Publications

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Journal Article
Working with Multilabel Datasets in R: The mldr Package, Charte, Francisco, and Charte David , The R Journal, Volume 7, Number 2, p.149–162, (2015) PDF icon 2015-RJournal-mldr.pdf (1.16 MB)
Web usage mining to improve the design of an e-commerce website: OrOliveSur.com, Carmona, C. J., Ramírez-Gallego S., Torres F., Bernal E., and del Jesus M. J. , Expert Systems with Applications, Volume 39, p.11243-11249, (2012) PDF icon 2012-Carmona-ESWA-I.pdf (907.1 KB)
Uso de dispositivos FPGA como apoyo a la enseñanza de asignaturas de arquitectura de computadores, Charte, Francisco, Espinilla Macarena, Rivera-Rivas A.J., and Pulgar-Rubio F. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 7, p.37–52, (2017) PDF icon 2017-EAIC17-FPGAsEnsenanza.pdf (1.48 MB)
Using fuzzy preference orderings in theta-dominance with application to health monitoring of Li-ion batteries, Echevarría, Yuviny, Couso Inés, Anseán David, Blanco Cecilio, and Sánchez Luciano , Journal of Multiple-Valued Logic and Soft Computing, (2017)
Using Evolutionary Algorithms as Instance Selection for Data Reduction in KDD: an Experimental Study, Cano, J. R., Herrera F., and Lozano M. , IEEE Transactions on Evolutionary Computation, Volume 7, Number 6, p.561-575, (2003)
Training set selection for monotonic ordinal classification, Cano, J. R., and García S. , Data & Knowledge Engineering, Volume 112, p.94 - 105, (2017)
Training algorithms for Radial Basis Function Networks to tackle learning processes with imbalanced data-sets, Pérez-Godoy, M.D., Rivera-Rivas A.J., Carmona C. J., and del Jesus M. J. , Applied Soft Computing, Volume 25, p.26-39, (2014) PDF icon 2014-Perez-ASOC.pdf (926.82 KB)
Tips, guidelines and tools for managing multi-label datasets: The mldr.datasets R package and the Cometa data repository, Charte, Francisco, Rivera-Rivas A.J., Charte David, del Jesus M. J., and Herrera F. , Neurocomputing, Volume 289, p.68–85, (2018) PDF icon 2018-Neucom-TipsMLCCometa-compressed.pdf (1017.86 KB)
Time Series Forecasting with KNN in R: the tsfknn Package, Martínez, Francisco, Frías María Pilar, Charte Francisco, and Rivera-Rivas A.J. , The R Journal, 12/2019, Volume 11, Number 2, p.229-242, (2019) PDF icon RJ-2019-004.pdf (204.01 KB)
Time series forecasting using evolutionary neural nets implemented in a volunteer computing system, Rivas, V.M., Parras-Gutiérrez E., Merelo J.J., Arenas M.G., and García-Fernández P. , Intelligent Systems in Accounting, Finance and Management, Volume 24, Number 2-3, p.87-95, (2017)
Time Series Forecasting by Generalized Regression Neural Networks Trained With Multiple Series, del Rio, Francisco Martínez, Frías M.P., Pérez-Godoy M.D., and Rivera-Rivas A.J. , IEEE Access, Volume 10, p.3275-3283, (2022)
The notion of roughness of a fuzzy set, Couso, Inés, Garrido Laura, and Sánchez Luciano , Fuzzy Sets and Systems, Volume 249, p.114 - 127, (2014)
The multi-LREP decomposition of solids and its application to a point-in-polyhedron inclusion test, Martínez, Francisco, Rueda Antonio, and Feito Francisco , The Visual Computer, 11, Volume 26, p.1361-1368, (2010)
The multi-L-REP decomposition and its application to a point-in-polygon inclusion test, Martínez, Francisco, Rueda Antonio, and Feito Francisco , Computers & Graphics, 12, Volume 30, p.947-958, (2006)
The Influence of Noise on the Evolutionary Fuzzy Systems for Subgroup Discovery, Luengo, J., García-Vico A.M., Pérez-Godoy M.D., and Carmona C. J. , Soft Computing, Volume 20, Issue 11, p.4313-4330, (2016) PDF icon 2016-Luengo-NoiseSD.pdf (972.31 KB)
The behavioral meaning of the median, Couso, Inés, Moral Serafín, and Sánchez Luciano , Information Sciences, Volume 294, p.127 - 138, (2015)
Temporal association rule mining: An overview considering the time variable as an integral or implied component, Segura‐Delgado, Alberto, Gacto M. J., Alcalá Rafael, and Alcalá-Fdez J. , WIREs Data Mining and Knowledge Discovery, 04/2020, Volume 10, Issue 4, (2020)
Taximeter verification with GPS and soft computing techniques, Villar, José, Otero Adolfo, Otero José, and Sánchez Luciano , Soft Computing, Mar, Volume 14, Number 4, p.405, (2009)
Taximeter verification using imprecise data from GPS, Villar, José, Otero Adolfo, Otero José, and Sánchez Luciano , Engineering Applications of Artificial Intelligence, Volume 22, Number 2, p.250 - 260, (2009)
Synthetic Sample Generation for Label Distribution Learning, Gonzalez, M, Luengo Julián, Cano J. R., and García Salvador , Information Sciences, 01/2021, Volume 544, p.197-213, (2021) PDF icon 1-s2.0-S0020025520307544-main.pdf (1.36 MB)
Supply Estimation Using Coevolutionary Genetic Algorithms in the Spanish Electrical Market, Marín, Enrique, and Sánchez Luciano , Applied Intelligence, 07, Volume 21, p.7-24, (2004)
Subgroup Discovery with Evolutionary Fuzzy Systems in R: the SDEFSR Package, García-Vico, A.M., Charte Francisco, González P., Carmona C. J., and del Jesus M. J. , The R Journal, Volume 8, Issue 2, p.307-323, (2016) PDF icon 2016-Garcia-RJournal.pdf (2.56 MB)
Subgroup Discovery on Multiple Instance Data, Luna, J. M., Carmona C. J., García-Vico A.M., del Jesus M. J., and Ventura S. , International Journal of Computational Intelligence Systems, 12/2019, Volume 12, Issue 2, p.1602-1612, (2019) PDF icon 125927212.pdf (1.91 MB)
Subgroup Discovery in Large Size Data Sets Preprocessed Using Stratified Instance Selection for Increasing the Presence of Minority Classes, Cano, J. R., García S., and Herrera F. , Pattern Recognition Letters, Volume 29, p.2156-2164, (2008)
Study on the use of different quality measures within a multi-objective evolutionary algorithm approach for emerging pattern mining in big data environments, García-Vico, A.M., González P., Carmona C. J., and del Jesus M. J. , Big Data Analytics, Volume 4, Number 1, p.1, (2019)
Study of the robustness of a meta-algorithm for the estimation of parameters in Radial Basis Function Neural Networks design, Parras-Gutiérrez, E., Rivas V. M., del Jesus M. J., and Merelo Juan J. , Neural Network World, Volume 19, Number 1, p.81-94, (2009)
Stratification for Scaling Up Evolutionary Prototype Selection, Cano, J. R., Herrera F., and Lozano M. , Pattern Recognition Letters, Volume 26, p.953-963, (2005)
Strategies for time series forecasting with generalized regression neural networks, Martínez, Francisco, Charte Francisco, Frías María Pilar, and Martínez-Rodríguez Ana María , Neurocomputing, Volume 491, p.509-521, (2022)
Special issue on genetic fuzzy systems and the interpretability-accuracy trade-off, Casillas, J., Herrera F., Pérez F.G.R., del Jesus M. J., and Villar P. , International Journal of Approximate Reasoning, Volume 44, p.1-3, (2007)
Some relationships between fuzzy and random set-based classifiers and models, Sánchez, Luciano, Casillas Jorge, Cordón O., and del Jesus M. J. , International Journal of Approximate Reasoning, Volume 29, Number 2, p.175 - 213, (2002)
Solving Multi-Class Problems with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning and Preference Relations, Fernández, A., Calderón M., Barrenechea E., Bustince H., and Herrera F. , Fuzzy Sets and Systems, Volume 161, Number 23, p.3064-3080, (2010)
Solving Electrical Distribution Problems Using Hybrid Evolutionary Data Analysis Techniques, Cordón, O., Herrera F., and Sánchez Luciano , Applied Intelligence, Jan, Volume 10, Number 1, p.5–24, (1999)
Smartdata: Data preprocessing to achieve smart data in R, Cordon, I., Luengo Julián, García Salvador, Herrera F., and Charte Francisco , Neurocomputing, 09/2019, Volume 360, p.1-13, (2019)
Singular spectral analysis of ill-known signals and its application to predictive maintenance of windmills with SCADA records, Sánchez, Luciano, and Couso Inés , Soft Computing, 05, Volume 16, (2011)
Similarity-based and Iterative Label Noise Filters for Monotonic Classification, Cano, J. R., Luengo Julián, and García Salvador , Proceedings of the 53rd Hawaii International Conference on System Sciences, p.1698-1706, (2020) PDF icon 0169.pdf (253.64 KB)
Similarity and dissimilarity measures between fuzzy sets: A formal relational study, Couso, Inés, Garrido Laura, and Sánchez Luciano , Inf. Sci., Volume 229, p.122-141, (2013)
Short, medium and long term forecasting of time series using the L-Co-R algorithm, Parras-Gutiérrez, E., Rivas V. M., Arenas M.G., and del Jesus M. J. , Neurocomputing, Volume 128, p.433-446, (2014)
Sequential pattern mining applied to aeroengine condition monitoring with uncertain health data, Palacios, Ana, Martínez Alvaro, Sánchez Luciano, and Couso Inés , Engineering Applications of Artificial Intelligence, Volume 44, p.10 - 24, (2015)
Ruta: implementations of neural autoencoders in R, Charte, David, Herrera F., and Charte Francisco , Knowledge-Based Systems, 06/2019, Volume 174, p.4-8, (2019) PDF icon 1-s2.0-S0950705119300140-main.pdf (421.73 KB)
Rule Base Reduction and Genetic Tuning of Fuzzy Systems based on the Linguistic 3-Tuples Representation, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Soft Computing, Volume 11, Number 5, p.401-419, (2007)
Revisiting Evolutionary Fuzzy Systems: Taxonomy, applications, new trends and challenges, Fernandez, Alberto, López Victoria, del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 80, p.109 - 121, (2015)
ReturnOK, la Wiki sobre retroinformática, Cabrera, Lina García, Ruano Ildefonso, Charte Francisco, Aguilar Andrés Molina, and Almagro José Ramón Bal , Iniciación a la Investigación, Volume 5, p.1-5, (2010) PDF icon 2010-IniciaInvUJA-ReturnOK.pdf (82.73 KB)
Replacement Strategies to Preserve Useful Diversity in Steady-State Genetic Algorithms, Lozano, M., Herrera F., and Cano J. R. , Information Sciences, (2012)
Replacement strategies to preserve useful diversity in steady-state genetic algorithms, Lozano, M., Cano J. R., and Herrera F. , Information Sciences, Volume 178, Number 23, p.4421–4433, (2008)
REMEDIAL-HwR: Tackling multilabel imbalance through label decoupling and data resampling hybridization, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 326, p.110–122, (2019) PDF icon 2019-NeucomRemedial-HwR.pdf (2.83 MB)
Reducing Data Complexity using Autoencoders with Class-informed Loss Functions, Charte, David, Charte Francisco, and Herrera Francisco , IEEE Transactions on Pattern Analysis and Machine Intelligence, Volume In Press, (2021)
Prototype selection to improve monotonic nearest neighbor, Cano, J. R., Aljohani Naif R., Abbasi Rabeeh Ayaz, Alowidbi Jalal S., and García S. , Engineering Applications of Artificial Intelligence, Volume 60, p.128 - 135, (2017)
Prototype Selection for Nearest Neighbor Classification: Taxonomy and Empirical Study, García, S., Derrac J., Cano J. R., and Herrera F. , IEEE Transactions Pattern Analysis and Machiche Intelligence, Volume 34, Number 3, p.417–435, (2012)
Propuesta de una asignatura de Diseño de Servidores para la especialidad de Tecnologías de Información, Rivera-Rivas, A.J., Espinilla Macarena, Fernández A., López José Santamarí, and Charte Francisco , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 4, p.15–24, (2014) PDF icon 2014-EAIC14-AsignaturaDisenoServ.pdf (864.57 KB)
ProLSFEO-LDL: Prototype Selection and Label- Specific Feature Evolutionary Optimization for Label Distribution Learning, Gonzalez, M, Cano J. R., and García Salvador , Applied Sciences, Volume 10, Issue 9, p.3089, (2020)
Preface: Special Issue on Genetic Fuzzy Systems and the Interpretability–Accuracy Trade-off, Casillas, Jorge, Herrera F., Pérez Raúl, and Villar P , International Journal of Approximate Reasoning, 01, Volume 44, p.1-3, (2007)
predtoolsTS: R package for streamlining time series forecasting, Charte, Francisco, Vico Alberto, Pérez-Godoy M.D., and Rivera-Rivas A.J. , Progress in Artificial Intelligence, 06/2019, Volume 8, p.505–510, (2019) PDF icon Charte2019_Article_PredtoolsTSRPackageForStreamli.pdf (390.07 KB)
Predictive-collaborative model as recovery and validation tool. Case of study: Psychiatric emergency department decision support, Cano, J. R. , Expert Systems with Applications, Volume 39, Number 4, p.4044–4048, (2012)
Overview on evolutionary subgroup discovery: analysis of the suitability and potential of the search performed by evolutionary algorithms, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , WIREs Data Mining and Knowledge Discovery, Volume 4, Number 2, p.87-103, (2014) PDF icon 2014-Carmona-WIRE-DMKD.pdf (958.42 KB)
On the influence of an adaptive inference system in fuzzy rule-based classification sytems for imbalanced data-sets, Fernández, A., Herrera F., and del Jesus M. J. , Expert Systems with Applications, Volume 36, Number 6, p.9805-9812, (2009)
On the discovery of association rules by means of evolutionary algorithms, del Jesus, M. J., Gámez José, González P., and Puerta Jose , Wiley Interdisc. Rew.: Data Mining and Knowledge Discovery, 09, Volume 1, Number 5, p.397-415, (2011)
On the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Applied Soft Computing, Volume 6, p.323-332, (2006)
On the 2-Tuples Based Genetic Tuning Performance for Fuzzy Rule Based Classification Systems in Imbalanced Data-Sets, Fernández, A., del Jesus M. J., and Herrera F. , Information Sciences, Volume 180, Number 8, p.1268-1291, (2010)
Obtaining transparent models of chaotic systems with multi-objective simulated annealing algorithms, Sánchez, Luciano, and Villar José R. , Information Sciences, Volume 178, Number 4, p.952 - 970, (2008)
Obtaining linguistic fuzzy rule-based regression models from imprecise data with multiobjective genetic algorithms, Sánchez, Luciano, Otero José, and Couso Inés , Soft Comput., 03, Volume 13, p.467-479, (2009)
Obtaining fuzzy rules from interval-censored data with genetic algorithms and a random sets-based semantic of the linguistic labels, Sánchez, Luciano, and Couso Inés , Soft Comput., 10, Volume 15, p.1945-1957, (2011)
Nuevas arquitecturas hardware de procesamiento de alto rendimiento para aprendizaje profundo, Rivera-Rivas, A.J., Charte Francisco, Espinilla Macarena, and Pérez-Godoy M.D. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 8, p.67–83, (2018) PDF icon 2018-EAIC18-HardwareAltoRend-compressed.pdf (431.68 KB)
NMEEF-SD: Non-dominated Multi-objective Evolutionary algorithm for Extracting Fuzzy rules in Subgroup Discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 18, Number 5, p.958-970, (2010) PDF icon 2010-Carmona-TFS.pdf (457.11 KB)
Niching scheme for steady state GA-P and its application to fuzzy rule based classifiers induction, Sánchez, Luciano, and González José Antonio Co , 01, (2000)
Mutual information-based feature selection and partition design in fuzzy rule-based classifiers from vague data, Sánchez, Luciano, M. Suárez Rosario, Villar J.R., and Couso Inés , International Journal of Approximate Reasoning, Volume 49, Number 3, p.607 - 622, (2008)
Multiobjective genetic classifier selection for random oracles fuzzy rule-based classifier ensembles: How beneficial is the additional diversity?, Trawiński, Krzysztof, Cordón O., Quirin Arnaud, and Sánchez Luciano , Knowledge-Based Systems, Volume 54, p.3 - 21, (2013)
Monotonic classification: An overview on algorithms, performance measures and data sets, Cano, J. R., Gutiérrez Pedro Antonio, Krawczyk Bartosz, Woźniak Michat, and García Salvador , Neurocomputing, 05/2019, Volume 341, p.168-182, (2019) PDF icon 1-s2.0-S0925231219302383-main.pdf (1.52 MB)
MoNGEL: monotonic nested generalized exemplar learning, García, Javier, Fardoun Habib M., Alghazzawi Daniyal M., Cano J. R., and García S. , Pattern Analysis and Applications, p.1–12, (2015)
MoNGEL: monotonic nested generalized exemplar learning, García, Javier, Fardoun Habib M., Alghazzawi Daniyal M., Cano J. R., and García S. , Pattern Analysis and Applications, May, Volume 20, Number 2, p.441–452, (2017)
MOGUL: A Methodology to Obtain Genetic fuzzy rule-based systems Ander the iterative rule Learning Approach, Cordón, O., del Jesus M. J., and Herrera F. , International Journal of Intelligent Systems, Volume 14, p.1123-1153, (1999)
MOEA-EFEP: Multi-Objective Evolutionary Algorithm for Extracting Fuzzy Emerging Patterns, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , IEEE Transaction on Fuzzy Systems, Volume 26, Issue 5, p.2861-2872, (2018)
Modelo predictivo colaborativo de apoyo al diagnóstico en servicio de urgencias psiquiátricas, Cano, J. R., González P., Aguilera José, López-Herrera A.G., Herrera F., Navío M., and Angel Jiménez-Arriero Miguel , Revista Ibérica de Sistemas y Tecnologías de la información, Volume 4, Number 4, p.29-42, (2009)
Modelado cualitativo utilizando una metodología evolutiva de aprendizaje iterativo de bases de reglas difusas, Cordón, O., del Jesus M. J., Herrera F., and Lozano M. , Revista Iberoamericana de Inteligencia Artificial, Volume 50, p.56-61, (1998)
MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 89, p.385–397, (2015) PDF icon 2015-KBS-MLSMOTE.pdf (1.56 MB)
Mining Fuzzy Association Rules from Low Quality Data, Palacios, A., Gacto M. J., and Alcalá-Fdez J. , Soft Computing, Volume 16, Number 5, p.883-901, (2012)
Mining Context-Aware Association Rules Using Grammar-Based Genetic Programming, Luna, J. M., Pechenizkiy M., del Jesus M. J., and Ventura S. , IEEE Transactions on Cybernetics, Nov, Volume 48, Number 11, p.3030-3044, (2018)
METSK-HDe: A Multiobjective Evolutionary Algorithm to learn accurate TSK-fuzzy Systems in High-Dimensional and Large-Scale Regression Problems, Gacto, M. J., Galende M., Alcalá R., and Herrera F. , Information Sciences, Volume 276, p.63–79, (2014) PDF icon 2014-MJGacto-METSK-HDe.pdf (792.59 KB)
MEFES: An evolutionary proposal for the detection of exceptions in subgroup discovery. An application to Concentrating Photovoltaic Technology, Carmona, C. J., González P., García-Domingo B., del Jesus M. J., and Aguilera J. , Knowledge-Based Systems, Volume 54, p.73-85, (2013) PDF icon 2013-Carmona-KBS.pdf (1.25 MB)
MEFASD-BD: Multi-Objective Evolutionary Algorithm for Subgroup Discovery in Big Data Environments - A MapReduce Solution, Pulgar-Rubio, F., Rivera-Rivas A.J., Pérez-Godoy M.D., González P., Carmona C. J., and del Jesus M. J. , Knowledge-Based Systems, Volume 117, p.70-78, (2017)
Mark-recapture techniques in statistical tests for imprecise data, Couso, Inés, and Sánchez Luciano , International Journal of Approximate Reasoning, Volume 52, Number 2, p.240 - 260, (2011)
Making CN2-SD Subgroup Discovery Algorithm scalable to Large Size Data Sets using Instance Selection, Cano, J. R., Herrera F., Lozano M., and García S. , Expert Systems with Applications, Volume 35, p.1949-1965, (2008)
Making CN1 -SD Subgroup Discovery Algorithm Scalable to Large Size Data Sets Using Instance Selection, Cano, J. R., Herrera F., Lozano Manuel, and García Salvador , Expert System with Applications, Volume 35, Number 4, p.1949-1965, (2008)
Machine learning models, epistemic set-valued data and generalized loss functions: An encompassing approach, Couso, Inés, and Sánchez Luciano , Information Sciences, Volume 358-359, p.129 - 150, (2016)
Localization and fuzzy classification of manufacturing defects in sheets of glass, Junco, Luis, and Sánchez Luciano , 01, Volume 5, (1998)
Local iterative DLT soft-computing vs. interval-valued stereo calibration and triangulation with uncertainty bounding in 3D reconstruction, Otero, José, and Sánchez Luciano , Neurocomputing, Volume 167, p.44 - 51, (2015)
Linguistic Modeling with Hierarchical Systems of Weighted Linguistic Rules, Alcalá, R., Cano J. R., Cordón O., Herrera F., Villar P., and Zwir I. , International Journal of Approximate Reasoning, Volume 32, Number 2-3, p.187-215, (2003)
Linguistic cost-sensitive learning of genetic fuzzy classifiers for imprecise data, Palacios, Ana M., Sánchez Luciano, and Couso Inés , International Journal of Approximate Reasoning, Volume 52, Number 6, p.841 - 862, (2011)
LI-MLC: A Label Inference Methodology for Addressing High Dimensionality in the Label Space for Multilabel Classification, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , IEEE Transactions on Neural Networks and Learning Systems, Volume 25, Number 10, p.1842-1854, (2014) PDF icon 2014-TNNLS-LI-MLC.pdf (1.85 MB)
Leveraging a predictive model of the workload for intelligent slot allocation schemes in energy-efficient HPC clusters, Cocaña-Fernández, Alberto, Sánchez Luciano, and Ranilla José , Engineering Applications of Artificial Intelligence, Volume 48, p.95 - 105, (2016)
Learning the Membership Function Contexts for Mining Fuzzy Association Rules by Using Genetic Algorithms, Alcalá-Fdez, J., Alcalá R., Gacto M. J., and Herrera F. , Fuzzy Sets and Systems, Volume 160, Number 7, p.905-921, (2009)
Learning from imprecise examples with GA-P algorithms, Sánchez, Luciano, and Couso Inés , Mathware & soft computing, ISSN 1134-5632, Vol. 5, Nº. 2-3, 1998, pags. 305-319, 01, Volume 5, (1998)
Label noise filtering techniques to improve monotonic classification, Cano, J. R., Luengo J., and García S. , Neurocomputing, 08/2019, Volume 353, p.83-95, (2019) PDF icon 1-s2.0-main.pdf (1.21 MB)
KEEL Data-Mining Software Tool: Data Set Repository, Integration of Algorithms and Experimental Analysis Framework, Alcalá-Fdez, J., Fernández A., Luengo J., Derrac J., García S., Sánchez L., and Herrera F. , Journal of Multiple-Valued Logic and Soft Computing, Volume 17, Number 2-3, p.255-287, (2011)
KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems, Alcalá-Fdez, J., Sánchez L., García S., del Jesus M. J., Ventura S., Garrell J.M., Otero J., Romero C., Bacardit J., Rivas V. M., et al. , Soft Computing, Volume 13, Number 3, p.307-318, (2009)
KEEL 3.0: An Open Source Software for Multi-Stage Analysis in Data Mining., Triguero, I., Gonzalez S., Moyano J.M., García S., Alcalá-Fdez J., Luengo J., Fernández A., del Jesus M. J., Sánchez L., Herrera F., et al. , International Journal of Computational Intelligence Systems, Volume 10, Number 1, p.1238-1249, (2017)
Is the average photon energy a unique characteristic of the spectral distribution of global irradiance?, Nofuentes, G, Gueymard CA, Aguilera J., Pérez-Godoy M.D., and Charte Francisco , Solar Energy, Volume 149, p.32–43, (2017) PDF icon 2017-SolarEnergy-Photon-compressed.pdf (534.33 KB)
Interval-valued GA-P algorithms, Sánchez, L. , IEEE Transactions on Evolutionary Computation, April, Volume 4, Number 1, p.64-72, (2000)
Interval-valued Blind Source Separation Applied to AI-based Prognostic Fault Detection of Aircraft Engines, Martinez, Alvaro, Sánchez Luciano, and Couso Inés , Journal of Multiple-Valued Logic and Soft Computing, 01, Volume 22, p.151-166, (2014)
Interpretability of Linguistic Fuzzy Rule-Based Systems: An Overview of Interpretability Measures, Gacto, M. J., Alcalá R., and Herrera F. , Information Sciences, Volume 181, Number 20, p.4340–4360, (2011)
Integration of an Index to Preserve the Semantic Interpretability in the Multi-Objective Evolutionary Rule Selection and Tuning of Linguistic Fuzzy Systems, Gacto, M. J., Alcalá R., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 18, Number 3, p.515-531, (2010)
Inner and outer fuzzy approximations of confidence intervals, Couso, Inés, and Sánchez Luciano , Fuzzy Sets and Systems, Volume 184, Number 1, p.68 - 83, (2011)
Induction of Fuzzy Rule Based Classifiers with Evolutionary Boosting Algorithms, del Jesus, M. J., Hoffmann F., Junco L., and Sánchez L. , IEEE Transactions on Fuzzy Systems, Volume 12, Number 3, p.296-308, (2004)
Induction of descriptive fuzzy classifiers with the Logitboost algorithm, Otero, José, and Sánchez Luciano , Soft Computing, Jul, Volume 10, Number 9, p.825–835, (2006)
Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning, Sanz, J., Fernández A., Bustince H., and Herrera F. , Information Sciences, Volume 180, Number 19, p.3674-3685, (2010)
Improving the Eco-Efficiency of High Performance Computing Clusters Using EECluster, Cocaña-Fernández, Alberto, Sánchez Luciano, and Ranilla, sr Jo , Energies, 03, Volume 9, p.197, (2016)
Improving Fuzzy Logic Controllers Obtained by Experts: A Case Study in HVAC Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Applied Intelligence, Volume 31, Number 1, p.15-30, (2009)
Improvement of subgroup descriptions in noisy data by detecting exceptions, González, P., García-Vico A.M., Carmona C. J., and del Jesus M. J. , Progress in Artificial Intelligence, Volume 7, Issue 1, p.55-64, (2018) PDF icon 2017-Gzlez-PRAI.pdf (371.57 KB)
IIVFDT: Ignorance Functions based Interval-Valued Fuzzy Decision Tree with Genetic Tuning. International Journal of Uncertainty, Sanz, J., Fernández A., and Bustince H. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, (2012)
Hyperrectangles Selection for Monotonic Classification by Using Evolutionary Algorithms, García, Javier, Al-bar Adnan, Aljohani Naif R., Cano J. R., and García S. , International Journal Computational Intelligence Systems, Volume 9, Number 1, p.184–201, (2016)
Higher order models for fuzzy random variables, Couso, Inés, and Sánchez Luciano , Fuzzy Sets and Systems, Volume 159, Number 3, p.237 - 258, (2008)
Hierarchical fuzzy rule based classfication systems with genetic rule selection for imbalanced data-sets, Fernández, A., del Jesus M. J., and Herrera F. , International Journal of Approximate Reasoning, Volume 50, p.561-577, (2009)
Harnessing the information contained in low-quality data sources, Couso, Inés, and Sánchez Luciano , Int. J. Approx. Reasoning, Volume 55, p.1485-1486, (2014)
GP-COACH: Genetic Programming-based learning of Compact and ACcurate fuzzy rule-based classification systems for High-dimensional problems, Berlanga, F.J., Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , Information Sciences, Volume 180, Number 8, p.1183 - 1200, (2010)
Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study, Fernández, A., Luengo J., García S., Bernadó-Mansilla E., and Herrera F. , IEEE Transactions on Evolutionary Computation, Volume 14, Number 6, p.913-941, (2010)
Genetic tuning of fuzzy rule deep structures preserving interpretability for linguistic modeling, Casillas, J., Cordón O., del Jesus M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 13, Number 1, p.13-29, (2005)
Genetic learning of the membership functions for mining fuzzy association rules from low quality data, Palacios, Ana María, Palacios José Luis, Sánchez Luciano, and Alcalá-Fdez Jesús , Information Sciences, Volume 295, p.358 - 378, (2015)
Genetic Learning of Fuzzy Rule-Based Classification Systems Cooperating with Fuzzy Reasoning Methods, Cordón, O., del Jesus M. J., and Herrera F. , International Journal of Intelligent Systems, Volume 13, Number 10/11, p.1025-1053, (1998)
Genetic lateral tuning for subgroup discovery with fuzzy rules using the algorithm NMEEF-SD, Carmona, C. J., González P., Gacto M. J., and del Jesus M. J. , International Journal of Computational Intelligence Systems, Volume 5, Number 2, p.355-367, (2012) PDF icon 2012-Carmona-IJCIS.pdf (747.67 KB)
Genetic Feature Selection in a Fuzzy Rule-Based Classification System Learning Process, Casillas, J., Cordón O., del Jesus M. J., and Herrera F. , Information Sciences, Volume 136, p.135-157, (2001)
Genetic feature selection in a fuzzy rule-based classification system learning process for high-dimensional problems, Casillas, J, Cordón O., del Jesus M. J., and Herrera F. , Information Sciences, Volume 136, Number 1, p.135 - 157, (2001)
Gamificación en procesos de autoentrenamiento y autoevaluación. Experiencia en la asignatura de Arquitectura de Computadores, Espinilla, M., Santamaría J, and Rivera-Rivas A.J. , Volume 6, p.55-65, (2016)
Fuzzy-genetic optimization of the parameters of a low cost system for the optical measurement of several dimensions of vehicles, Otero, J., Sánchez L., and Alcalá-Fdez J. , Soft Computing, Jun, Volume 12, Number 8, p.751–764, (2008)
Fuzzy Rules for Describing Subgroups from Influenza A Virus Using a Multi-objective Evolutionary Algorithm, Carmona, C. J., Chrysostomou C., Seker H., and del Jesus M. J. , Applied Soft Computing, Volume 13, p.3439-3448, (2013) PDF icon 2013-Carmona-ASOC.pdf (1000.39 KB)
Future Performance Modeling in Athletism with Low Quality Data-based Genetic Fuzzy Systems, Palacios, Ana, Sánchez Luciano, and Couso Inés , Multiple-Valued Logic and Soft Computing, 01, Volume 17, p.207-228, (2011)
Finding informative code metrics under uncertainty for predicting the pass rate of online courses, Otero, José, Junco Luis, Suárez Rosario, Palacios Ana, Couso Inés, and Sánchez Luciano , Information Sciences, Volume 373, p.42 - 56, (2016)
FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams, García-Vico, A.M., Carmona C. J., González P., Seker H., and del Jesus M. J. , IEEE Transactions on Fuzzy Systems, 12/2020, Volume 28, Issue 12, p. 3193-3203, (2020) PDF icon 09088291.pdf (1.29 MB)
Feature Selection and Granularity Learning in Genetic Fuzzy Rule-Based Classication Systems for Highly Imbalanced Data-Sets, Villar, P., Fernández A., Carrasco R., and Herrera F. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 20, Number 3, p.369-397, (2012)
Extending a simple genetic cooperative-competitive learning fuzzy classifier to low quality datasets, Palacios, Ana, Sánchez Luciano, and Couso Inés , Evolutionary Intelligence, 11, Volume 2, p.73-84, (2009)
Explotación de la potencia de procesamiento mediante paralelismo: un recorrido histórico hasta la GPGPU, Charte, Francisco, Rivera-Rivas A.J., Pulgar-Rubio F., and Díaz María J. del Jesu , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 6, p.19–33, (2016) PDF icon 2016-EAIC16-Paralelismo.pdf (1.16 MB)
Experimental Study on 164 Algorithms Available in Software Tools for Solving Standard Non-Linear Regression Problems, Gacto, M. J., Soto-Hidalgo Jose Manuel, Alcalá-Fdez J., and Alcalá Rafael , IEEE Access, 08/2019, Volume 7, p. 108916-108939, (2019)
Evolutionary-Based Selection of Generalized Instances for Imbalanced Classification, García, S., Derrac J., Triguero I., Carmona C. J., and Herrera F. , Knowledge-Based Systems, Volume 25, Number 1, p.3-12, (2012) PDF icon 2012-Garcia-KBS.pdf (522.95 KB)
Evolutionary Stratified Training Set Selection for Extracting Classification Rules with trade off Precision-Interpretability, Cano, J. R., Herrera F., and Lozano M. , Data & Knowledge Engineering, Volume 60, Number 1, p.90-108, (2007)
Evolutionary Stratified Instance Selection applied to Training Set Selection for Extracting High Precise-Interpretable Classification Rules, Cano, J. R., Herrera F., and Lozano Manuel , 01, (2008)
Evolutionary Selection of Hyperrectangles in Nested Generalized Exemplar Learning, García, S., Derrac J., Luengo J., Carmona C. J., and Herrera F. , Applied Soft Computing, Volume 11, Number 3, p.3032-3045, (2011) PDF icon 2011-Garcia-ASOC.pdf (2.07 MB)
Evolutionary Fuzzy Sistems for Explainable Artificial Intelligence: Why, When, What for, and Where to ?, Fernández, A., del Jesus M. J., Cordón O., Marcelloni F., and Herrera F. , IEEE Computational Intelligence, Volume 1, Number 14, p.69-81, (2019) PDF icon 08610271.pdf (1.09 MB)
Evolutionary fuzzy rule induction process for subgroup discovery: a case study in marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , IEEE Transactions on Fuzzy Systems, Volume 15, Number 4, p.578-592, (2007)
Evolutionary Fuzzy Rule Extraction for Subgroup Discovery in a Psychiatric Emergency Department, Carmona, C. J., González P., del Jesus M. J., Navío M., and Jiménez L. , Soft Computing, Volume 15, Number 12, p.2435-2448, (2011) PDF icon 2011-Carmona-SoCo.pdf (280.17 KB)
Evolutionary Data Mining and Applications: A Revision on the Most Cited Papers from the Last 10 Years (2007-2017), Alcalá, R., Gacto M. J., and Alcalá-Fdez J. , WIREs Data Mining and Knowledge Discover, Volume 8, p.1-17, (2018)
Evolutionary and metaheuristics based data mining, del Jesus, M. J., Gámez J.A., and Puerta J.M. , Soft Computing: a fusion of methodologies and applications, Volume 13, p.209-212, (2009)
Evolutionary algorithms for subgroup discovery in e-learning: A practical application using Moodle data, Romero, C., González P., Ventura S., del Jesus M. J., and Herrera F. , Expert Systems with Applications, Volume 36, p.1632-1644, (2009)
Evolución tecnológica del hardware de vídeo y las GPU en los ordenadores personales, Charte, Francisco, Rueda Antonio J., Espinilla Macarena, and Rivera-Rivas A.J. , Enseñanza y aprendizaje de ingeniería de computadores. Revista de experiencias docentes en ingeniería de computadores, Volume 7, p.111–128, (2017) PDF icon 2017-EAIC17-EvolucionGPUs.pdf (2.1 MB)
EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search, Charte, Francisco, Rivera-Rivas A.J., Martínez Francisco, and del Jesus M. J. , Integrated Computer-Aided Engineering, 05/2020, Volume 27, Number 3, p.211-231, (2020) PDF icon FCharte-EvoAAAOpen.pdf (820.83 KB)
Enhancing the Effectiveness and Interpretability of Decision Tree and Rule Induction Classifiers with Evolutionary Training Set Selection over Imbalanced Problems, García, S., Fernández A., and Herrera F. , Applied Soft Computing, Volume 9, p.1304-1314, (2009)
Enhancing instance-level constrained clustering through differential evolution, González-Almagro, Germán, Luengo Julián, Cano J. R., and García Salvador , Applied Soft Computing, Volume 108, Number 107435, p.1-19, (2021)
Eliciting a human understandable model of ice adhesion strength for rotor blade leading edge materials from uncertain experimental data, Palacios, Ana M., Palacios José L., and Sánchez Luciano , Expert Systems with Applications, Volume 39, Number 11, p.10212 - 10225, (2012)
El ecosistema de aprendizaje del estudiante universitario en la post-pandemia. Metodologías y herramientas, Charte, Francisco, Rivera-Rivas A.J., Medina J., and Espinilla Macarena , Enseñanza y Aprendizaje de Ingeniería de Computadores, Number 10, (2020)
E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments, García-Vico, A.M., Charte Francisco, González P., Elizondo D., and Carmona C. J. , Neurocomputing, 11/2020, Volume 415, p.60-73, (2020) PDF icon 1-s2.0-S0925231220311139-main.pdf (927.85 KB)
Disenos experimentales y tests estadisticos, tendencias actuales en Machine Learning., Otero, J, and Sánchez Luciano , 01, (2007)
DILS: Constrained clustering through dual iterative local search, González-Almagro, Germán, Luengo Julián, Cano J. R., and García Salvador , Computers & Operations Research, Volume 121, p.104979, (2020) PDF icon 1-s2.0-S0305054820300964-main.pdf (903.73 KB)
Diagnose of Effective Evolutionary Prototype Selection using an Overlapping Measure, García, S., Cano J. R., Bernadó-Mansilla E., and Herrera F. , International Journal of Pattern Recognition and Artificial Intelligence, Volume 23, Number 8, p.1527-1548, (2009)
DGLMExtPois: Advances in Dealing with Over and Under-dispersion in a Double GLM Framework, Sáez-Castillo, Antonio J., Conde-Sánchez Antonio, and Martínez Francisco , The R Journal, Volume 14, Number 4, p.121-140, (2022)
Detecting hidden periodicities for models with cyclical errors, Frías, M.P., Ivanov Alexander, Leonenko Nikolai, Martínez Francisco, and Ruiz-Medina María Dolores , Statistics and Its Interface, 04, Volume 10, Number 1, p.107-118, (2017)
Design of RBF Networks by Cooperative/Competitive Evolution of Units, Rivas, Antonio Rivera, Ortega Julio, and Prieto A , 04, (2001)
Decomposition-Fusion for Label Distribution Learning, Gonzalez, M, González-Almagro Germán, Triguero Isaac, Cano J. R., and García Salvador , Information Fusion, 02/2021, Volume 66, p.64-75, (2021) PDF icon 1-s2.0-S1566253520303596-main.pdf (947.74 KB)
Dealing with seasonality by narrowing the training set in time series forecasting with kNN, Martínez, Francisco, Frías María Pilar, Pérez-Godoy M.D., and Rivera-Rivas A.J. , Expert Systems with Applications, Volume 103, p.38 - 48, (2018)
Dealing with difficult minority labels in imbalanced mutilabel data sets, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 326, p.39–53, (2019) PDF icon 2019-NeucomDealingDifficultLabels.pdf (4.77 MB)
Cost-Sensitive Learning of Fuzzy Rules for Imbalanced Classification Problems Using FURIA, Palacios, Ana, Trawinski Krzysztof, Cordón O., and Sánchez Luciano , International Journal of Uncertainty Fuzziness and Knowledge-Based Systems, 10, Volume 22, p.643-675, (2014)
Comparison of response surface methodology and artificial neural network applied to enzymatic hydrolysis of rapeseed straw, Castro, E., Cara C., del Jesus M. J., and Rivas V. M. , Journal of Biotechnology, Volume 150, p.137, (2010)
Comparison and Design of Interpretable Linguistic vs. Scatter FRBSs: GM3M Generalization and New Rule Meaning Index (RMI) for Global Assessment and Local Pseudo-Linguistic Representation, Galende, M., Gacto M. J., Sainz G., and Alcalá R. , Information Sciences, Volume 282, p.190–213, (2014)
Comparative analysis of data mining and response surface methodology predictive models for enzymatic hydrolysis of pretreated olive tree biomass, Charte, Francisco, Romero Inmaculada, Pérez-Godoy M.D., Rivera-Rivas A.J., and Castro Eulogio , Computers & Chemical Engineering, Volume 101, p.23–30, (2017) PDF icon 2017-CACE-Biomasa.pdf (1.28 MB)
CommuniMents: A Framework for Detecting Community Based Sentiments for Events, Jarwar, Muhammad Aslam, Abbasi Rabeeh Ayaz, Mushtaq Mubashar, Maqbool Onaiza, Aljohani Naif R., Daud Ali, Alowibdi Jalal S., Cano J. R., García Salvador, and Chong Ilyoung , International Journal on Semantic Web and Information Systems, Volume 13, Issue 2, p.87-108, (2017)
Comments on “Learning from imprecise and fuzzy observations: Data disambiguation through generalized loss minimization” by Eyke Hüllermeier, Sánchez, Luciano , International Journal of Approximate Reasoning, Volume 55, Number 7, p.1583 - 1587, (2014)
Combining GP operators with SA search to evolve fuzzy rule based classifiers, Sánchez, Luciano, Couso Inés, and Corrales J.A. , Information Sciences, Volume 136, Number 1, p.175 - 191, (2001)
COMBINING ADABOOST WITH PREPROCESSING ALGORITHMS FOR EXTRACTING FUZZY RULES FROM LOW QUALITY DATA IN POSSIBLY IMBALANCED PROBLEMS, Palacios, Ana, Sánchez Luciano, and Couso Inés , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 20, Number supp02, p.51-71, (2012)
Coevolution of lags and RBFNs for time series forecasting: L-Co-R algorithm, Parras-Gutiérrez, E., García-Arenas M., Rivas V. M., and del Jesus M. J. , Soft Computing, Volume 16, Number 6, p.919-942, (2012)
CO2RBFN for short-term forecasting of the extra virgin olive oil price in the Spanish market, Pérez-Godoy, M.D., Pérez P., Rivera-Rivas A.J., del Jesus M. J., Carmona C. J., Frías M.P., and Parras M. , International Journal of Hybrid Intelligent Systems, p.75-87, (2010) PDF icon 2010-Perez-Godoy-IJHIS.pdf (434.9 KB)
CO2RBFN: An evolutionary cooperative-competitive RBFN design algorithm for classification problems, Pérez-Godoy, M.D., Rivas Antonio Rivera, Berlanga Francisco J., and del Jesus M. J. , Soft Computing, 07, Volume 14, p.953-971, (2009)
Clustering: An R library to facilitate the analysis and comparison of cluster algorithms, Pérez-Martos, L.A., García-Vico A.M., González P., and Carmona C. J. , Progress in Artificial Intelligence, (In Press)
ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders, Pulgar, Francisco J., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. , Information Sciences, Volume 565, p.146-176, (2021) PDF icon 1-s2.0-S0020025521002024-main.pdf (1.79 MB)
Choosing the proper autoencoder for feature fusion based on data complexity and classifiers: Analysis, tips and guidelines, Pulgar, Francisco J., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. , Information Fusion, 02/2020, Volume 54, p.44-60, (2020) PDF icon 1-s2.0-S1566253519300880-main.pdf (895.14 KB)
Characterization of Concentrating Photovoltaic modules by cooperative competitive Radial Basis Function Networks, Rivas, Antonio Rivera, García-Domingo B., del Jesus M. J., and Aguilera J. , Expert Systems with Applications, 04, Volume 40, Number 05, p.1599–1608, (2013)
Bootstrap analysis of multiple repetitions of experiments using an interval-valued multiple comparison procedure, Otero, José, Sánchez Luciano, Couso Inés, and Palacios Ana , Journal of Computer and System Sciences, Volume 80, Number 1, p.88 - 100, (2014)
Boosting fuzzy rules in classification problems under single-winner inference, Sánchez, Luciano, and Otero José , Int. J. Intell. Syst., Volume 22, p.1021-1034, (2007)
Big Data with Cloud Computing: an insight on the computing environment, MapReduce, and programming frameworks, Fernández, Alberto, del Río Sara, López Victoria, Bawakid Abdullah, del Jesus M. J., Benitez Jose M., and Herrera F. , WIREs Data Mining and Knowledge Discovery, Volume 4, Number 5, p.380-409, (2014)
Automatic Laser Pointer Detection Algorithm for Environment Control Device Systems Based on Template Matching and Genetic Tuning of Fuzzy Rule-Based Systems, Chávez, F., Fernández A., Gacto M. J., and Alcalá R. , International Journal of Computational Intelligence Systems, Volume 5, Number 2, p.368-386, (2012)
Assessing the differences in accuracy between GFSs with bootstrap tests, Sánchez, Luciano, and Alcala-Fdez Jesus , 01, (2005)
Artificial intelligence within the interplay between natural and artificial computation: Advances in data science, trends and applications, M.Górriz, Juan, Ramírez Javier, Ortíz Andrés, Martínez-Murcia Francisco J., Segovia Fermín, Suckling John, Leming Matthew, Zhang Yu-Dong, Álvarez-Sánchez José Ramón, Bologna Guido, et al. , Neurocomputing, Volume 410, p.237-270, (2020)
Applying multiobjective RBFNNs optimization and feature selection to a mineral reduction problem, Guillén, Alberto, Rubio Gines, Toda I, Rivas Antonio Rivera, Pomares Hector, and Ruiz Ignacio Rojas , Expert Syst. Appl., 06, Volume 37, p.4050-4057, (2010)
Analyzing the Reasoning Mechanisms in Fuzzy Rule-Based Classification Systems, Cordón, O., del Jesus M. J., and Herrera F. , Mathware & Soft Computing, Volume 5, p.321-332, (1999)
Analyzing the Reasoning Mechanism in Fuzzy Rule-Based Classification Systems, Cordón, O., del Jesus M. J., and Herrera F. , Mathware & Soft Computing, Volume 5, p.321-332, (1998)
Analysis of preprocessing vs. cost-sensitive learning for imbalanced classification. Open problems on intrinsic data characteristics, López, V., Fernández A., Moreno-Torres J.G., and Herrera F. , Expert Systems with Applications, Volume 39, Number 7, p.6585-6608, (2012)
Analysis of data complexity measures for classification, Cano, J. R. , Expert Systems with Applications, Volume 40, Number 12, p.4820–4831, (2013)
Analysis of an evolutionary RBFN design algorithm, CO2RBFN, for imbalanced data sets, Pérez-Godoy, M.D., Fernández Alberto, Rivas Antonio Rivera, and del Jesus M. J. , Pattern Recognition Letters, 11, Volume 31, Number 15, p.2375-2388, (2010)
Analysing the classification of imbalanced data-sets with multiple classes: Binarization techniques and ad-hoc approaches, Fernandez, Alberto, López Victoria, Galar Mikel, del Jesus M. J., Herrera F., and BV ELSEVIER S. C. I. E. N. C. E. , Knowledge-Based Systems, Volume 42, p.97 - 110, (2013)
An overview on Subgroup Discovery: Foundations and Applications, Herrera, F., Carmona C. J., González P., and del Jesus M. J. , Knowledge and Information Systems, Volume 29, Number 3, p.495-525, (2011) PDF icon 2011-Herrera-KAIS.pdf (553.73 KB)
An Overview of Emerging Pattern Mining in Supervised Descriptive Rule Discovery: Taxonomy, Empirical Study, Trends and Prospects, García-Vico, A.M., Carmona C. J., Martín D., García-Borroto M., and del Jesus M. J. , WIREs Data Mining and Knowledge Discovery, Volume 8, Issue 1, (2018) PDF icon 2018-Garcia-Wiley.pdf (728.97 KB)
An Internet of Things and Fuzzy Markup Language Based Approach to Prevent the Risk of Falling Object Accidents in the Execution Phase of Construction Projects, Rojas, María Martínez, Gacto M. J., Vitiello Autilia, Acampora Giovanni, and Hidalgo José Manuel Sot , Sensors, Volume 21, Number 19, p.6461, (2021)
An extension of the FURIA classification algorithm to low quality data through fuzzy rankings and its application to the early diagnosis of dyslexia, Palacios, Ana, Sánchez Luciano, Couso Inés, and Destercke Sébastien , Neurocomputing, Volume 176, p.60 - 71, (2016)
An Equivalent Circuit Model With Variable Effective Capacity for LiFePO4 Batteries, Blanco, Cecilio, Sánchez Luciano, Gonzalez M, Antón Juan Carlos, Fernández Víctor García, and Viera Juan , IEEE Transactions on Vehicular Technology, 10, Volume 63, p.3592-3599, (2014)
An analysis on the use of pre-processing methods in evolutionary fuzzy systems for subgroup discovery, Carmona, C. J., Luengo J., González P., and del Jesus M. J. , Expert Systems with Applications, Volume 39, p.11404-11412, (2012) PDF icon 2012-Carmona-ESWA-II.pdf (468.94 KB)
An analysis on the use of autoencoders for representation learning: Fundamentals, learning task case studies, explainability and challenges, Charte, David, Charte Francisco, del Jesus M. J., and Herrera F. , Neurocomputing, Volume 404, p.93-107, (2020) PDF icon 1-s2.0-S092523122030624X-main.pdf (0 bytes)
An analysis of technological frameworks for data streams, Puentes, F., Pérez-Godoy M.D., González P., and del Jesus M. J. , Progress in Artificial Intelligence, 06/2020, Volume 9, p.239–261, (2020)
AEkNN: An AutoEncoder kNN-Based Classifier With Built-in Dimensionality Reduction, Pulgar-Rubio, F., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. , International Journal of Computational Intelligence Systems, 11/2018, Volume 12, p.436-452, (2018) PDF icon 125905686.pdf (3.86 MB)
Advocating the Use of Imprecisely Observed Data in Genetic Fuzzy Systems, Sánchez, L., and Couso I. , IEEE Transactions on Fuzzy Systems, Aug, Volume 15, Number 4, p.551-562, (2007)
Advanced nonparametric tests for multiple comparisons in the design of experiments in computational intelligence and data mining: Experimental Analysis of Power, García, S., Fernández A., Luengo J., and Herrera F. , Information Sciences, Volume 180, p.2044–2064, (2010)
Addressing Imbalanced Classification with Instance Generation Techniques: IPADE-ID, López, V., Triguero I., Carmona C. J., García S., and Herrera F. , Neurocomputing, Volume 126, p.15-28, (2014) PDF icon 2014-Lopez-NEUROCOMPUTING.pdf (933.25 KB)
Addressing imbalance in multilabel classification: Measures and random resampling algorithms, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , Neurocomputing, Volume 163, p.3–16, (2015) PDF icon 2015-Neucom-AddressingImbalance.pdf (546.81 KB)
Addressing Data Complexity for Imbalanced Data Sets: Analysis of SMOTE-based Oversampling and Evolutionary Undersampling, Luengo, J., Fernández A., García S., and Herrera F. , Soft Computing, Volume 15, Number 10, p.1909-1936, (2011)
Additive similarity and dissimilarity measures, Couso, Inés, and Sánchez Luciano , Fuzzy Sets and Systems, Volume 322, p.35 - 53, (2017)
Adaptation and Application of Multi-Objective Evolutionary Algorithms for Rule Reduction and Parameter Tuning of Fuzzy Rule-Based Systems, Gacto, M. J., Alcalá R., and Herrera F. , Soft Computing, Volume 13, Number 5, p.419-436, (2009)
A View on Fuzzy Systems for Big Data: Progress and Opportunities, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , International Journal of Computational Intelligence Systems, Volume 9, Number 1, p.69-80, (2016) PDF icon 2016-Fernandez-IJCIS.pdf (455.58 KB)
A Unifying Analysis for the Supervised Descriptive Rule Discovery via the Weighted Relative Accuracy, Carmona, C. J., del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 139, p.89-100, (2018) PDF icon 2018-Carmona-KBS.pdf (1.57 MB)
A study on the medium-term forecasting using exogenous variable selection of the extra-virgin olive oil with soft computing methods, Rivera-Rivas, A.J., Pérez-Recuerda Pedro, Pérez-Godoy M.D., del Jesus M. J., Frías María Pilar, and Parras Manuel , Applied Intelligence, Jun, Volume 34, Number 3, p.331–346, (2011)
A Study of the Behaviour of Linguistic Fuzzy Rule Based Classification Systems in the Framework of Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Fuzzy Sets and Systems, Volume 159, Number 18, p.2378-2398, (2008)
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations, Charte, David, Charte Francisco, García S., and Herrera F. , Progress in Artificial Intelligence, 11, Volume 8, p.1-14, (2019) PDF icon 2018-PRAI-NonStandard-Accepted.pdf (951.61 KB)
A snapshot on nonstandard supervised learning problems: taxonomy, relationships, problem transformations and algorithm adaptations, Charte, David, Charte Francisco, García S., and Herrera F. , Progress in Artificial Intelligence, Nov, (2018)
A Review on Ensembles for Class Imbalance Problem: Bagging, Boosting and Hybrid Based Approaches, Galar, M., Fernández A., Barrenechea E., Bustince H., and Herrera F. , IEEE Transactions on System, Man and Cybernetics - Part C: Applications and Reviews, Volume 42, Number 4, p.463-484, (2012)
A random sets-based method for identifying fuzzy models, Sánchez, Luciano , Fuzzy Sets and Systems, Volume 98, Number 3, p.343 - 354, (1998)
A proposal on Reasoning Methods in Fuzzy Rule-Based Classification Systems, Cordón, O., del Jesus M. J., and Herrera F. , International Journal of Approximate Reasoning, Volume 20, p.21-45, (1999)
A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , International Journal of Neural Systems, Volume 27, Issue 6, p.1-17, (2017) PDF icon 2017-Fernandez-IJNS.pdf (683.56 KB)
A new hybrid methodology for cooperative-coevolutionary optimization of radial basis function networks, Rivera-Rivas, A.J., Rojas I., Ortega J., and del Jesus M. J. , Soft Computing, May, Volume 11, Number 7, p.655–668, (2007)
A new algorithm for computing Boolean operations on polygons, Martínez, Francisco, Rueda Antonio Jesús, and Feito Francisco Ramón , Computers & Geosciences, Volume 35, Number 6, p.1177 - 1185, (2009)
A Multi-objectiveGenetic Algorithm for Tuning and Rule Selection to Obtain Accurate and Compact Linguistic Fuzzy Rule-Based Systems, Alcalá, R., Gacto M. J., Herrera F., and Alcalá-Fdez J. , International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems, Volume 15, Number 5, p.539–557, (2007)
A Multi-Objective Evolutionary Algorithm for an Effective Tuning of Fuzzy Logic Controllers in Heating, Ventilating and Air Conditioning Systems, Gacto, M. J., Alcalá R., and Herrera F. , Applied Intelligence, Volume 36, Number 2, p.330-347, (2012)
A methodology for exploiting the tolerance for imprecision in genetic fuzzy systems and its application to characterization of rotorblade leading edge materials, Sánchez, Luciano, Couso Inés, Palacios Ana, and Palacios José , Mechanical Systems and Signal Processing, 06, Volume 37, p.76-91, (2013)
A methodology for applying k-nearest neighbor to time series forecasting, Martínez, Francisco, Frías María Pilar, Pérez-Godoy M.D., and Rivera-Rivas A.J. , Artificial Intelligence Review, Nov, (2017)
A memetic algorithm for Evolutionary Prototype Selection: A Scaling Up Approach, García, S., Cano J. R., and Herrera F. , Pattern Recognition, Volume 41, Number 8, p.2693-2709, (2008)
A hierarchical genetic fuzzy system based on genetic programming for addressing classification with highly imbalanced and borderline data-sets, López, Victoria, Fernandez Alberto, del Jesus M. J., and Herrera F. , Knowledge-Based Systems, Volume 38, p.85 - 104, (2013)
A greedy randomized adaptive search procedure applied to the clustering problem as an initialization process using K-Means as a local search procedure, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Journal of Intelligent and Fuzzy Systems, Volume 12, Number 3-4, p.235–242, (2002)
A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position, Sanz, J., Fernández A., Bustince H., and Herrera F. , International Journal of Approximate Reasoning, Volume 52, Number 6, p.751-766, (2011)
A Genetic Fuzzy Linguistic Combination Method for Fuzzy Rule-based Multiclassifiers Revista: IEEE Transactions on Fuzzy Systems, Cordón, O., Sánchez Luciano, Quirin Arnaud, and Trawinski Krzysztof , IEEE Transactions on Fuzzy Systems, 01, Volume 21, Number 5, p.950-965, (2013)
A fuzzy genetic programming-based algorithm for subgroup discovery and the application to one problem of pathogenesis of acute sore throat conditions in humans, Carmona, C. J., Ruiz-Rodado V., del Jesus M. J., Weber A., Grootveld M., González P., and Elizondo D. , Information Sciences, Volume 298, p.180-197, (2015) PDF icon 2015-Carmona-INS.pdf (814.28 KB)
A fast genetic method for inducting descriptive fuzzy models, Sánchez, Luciano, and Otero José , Fuzzy Sets and Systems, 01, Volume 141, p.33-46, (2004)
A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems, Alcalá, R., Gacto M. J., and Herrera F. , IEEE Transactions on Fuzzy Systems, Volume 19, Number 4, p.666-681, (2011)
A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , Information Fusion, (In Press)
A differential evolution proposal for estimating the maximum power delivered by CPV modules under real outdoor conditions, García-Domingo, B., Carmona C. J., Rivera-Rivas A.J., del Jesus M. J., and Aguilera J. , Expert Systems with Applications, Volume 42, Number 13, p.5452–5462, (2015) PDF icon 2015-GarciaDomingo-ESWA.pdf (1.22 MB)
A design methodology for semi-physical fuzzy models applied to the dynamic characterization of LiFePO4 batteries, Sánchez, Luciano, Couso Inés, and González Manuela , Applied Soft Computing, Volume 14, p.269 - 288, (2014)
A Comprehensive and Didactic Review on Multilabel Learning Software Tools, Charte, Francisco , IEEE Access, 03/2020, Volume 8, p.50330-50354, (2020)
A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , Expert Systems with Applications, Volume 183, Issue C, p.115419, (2021) PDF icon 2021-Garcia-ESWA.pdf (1.29 MB)
A Big Data Approach for the Extraction of Fuzzy Emerging Patterns, García-Vico, A.M., González P., Carmona C. J., and del Jesus M. J. , Cognitive Computation, 01/2019, Volume 11, p.400–417, (2019) PDF icon García-Vico2019_Article_ABigDataApproachForTheExtracti.pdf (1.1 MB)
3D motion estimation of bubbles of gas in fluid glass, using an optical flow gradient technique extended to a third dimension, Otero, J., Otero A., and Sánchez L. , Machine Vision and Applications, Jul, Volume 14, Number 3, p.185–191, (2003)
Conference Paper
Web Browser-Based Forecasting of Economic Time-Series, Rivas, V. M., Parras-Gutiérrez E., Merelo J. J., Arenas M. G., and García-Fernández P. , Decision Economics, In Commemoration of the Birth Centennial of Herbert A. Simon 1916-2016 (Nobel Prize in Economics 1978), Cham, p.35–42, (2016)
Utilización de un sistema basado en reglas difusas para la aplicación de operadores en un algoritmo cooperativo-competitivo, Pérez-Godoy, M.D., Rivas Antonio Rivera, José Rivas M., Díaz Jesus, José F, and Rivera Berlanga , XIV Congreso Español sobre tecnologías y logica fuzzy, 09, Cuencas Mineras Asturianas, (2008)
Utilización de Algoritmos Genéticos Multiobjetivos para la Selección de Características y Diseño de la Base de Conocimiento de un Sistema de Clasificación Basado en Reglas Difusas, Cordón, O., Herrera F., Díaz María José del, Magdalena Luis, Sánchez A.M., and Villar Pedro , Congreso Español sobre Tecnologías y Lógica Fuzzy, 01, León (España), (2002)
Uso de metodologías de aprendizaje invertido para resolución de la parte práctica en asignaturas del grado de ingeniería informática, Carmona, C. J., González P., and García-Vico A.M. , XX Congreso Internacional de Investigación Educativa (14-17 de junio), Santiago de Compostela, (2022)
Using the adabooth algorithm to induce fuzzy rules in classification problems, Junco, Luis, and Sánchez Luciano , X Congreso Español sobre Tecnologías y Lógica Difusa, 09, Santander (España), (2000)
Using the Adaboost algorithm for extracting fuzzy rules from low quality data: Some preliminary results, Palacios, A. M., Sánchez L., and Couso I. , 2011 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), June, p.1263-1270, (2011)
Using a symbolic model checker for verify safety properties in SA/RT models, Tuya, Javier, Sánchez Luciano, and Corrales Jose A. , Software Engineering –- ESEC '95, Berlin, Heidelberg, p.59–75, (1995)
Usando Algoritmos de Descubrimiento de Subgrupos en R: El Paquete SDR, García-Vico, A.M., Charte Francisco, González P., Carmona C. J., and del Jesus M. J. , VII Simposio de Teoría y Aplicaciones de Minería de Datos, p.739-748, (2015) PDF icon 2015 - TAMIDA-b.pdf (335 KB)
Universol Project. Final Results, del Jesus, M. J., and De La Casa-Higueras Juan , 26 th European Photovoltaic Solar Energy Conference, 01, Hamburgo, Alemania, (2012)
Una propuesta para la formación en las tecnologías Web, Rivera-Rivas, A.J., and Balsas José R. , Nuevas tecnologías aplicadas a la educación, 11, (2000)
Una primera aproximación para la extracción de patrones emergentes en flujos continuos de datos, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), Mejor trabajo del II Workshop en Big Data y Análisis de Datos Escalable - BigDADE 2018, p.1093-1098, (2018) PDF icon 2018_Garcia_BigDADE.pdf (129.48 KB)
Una primera aproximación al descubrimiento de subgrupos bajo el paradigma MapReduce, Pulgar-Rubio, F., Carmona C. J., Rivera-Rivas A.J., González P., and del Jesus M. J. , 1er Workshop en Big Data y Análisis de Datos Escalable, p.991-1000, (2015) PDF icon 2015 - BD.pdf (374.17 KB)
Una primera aproximación a la predicción de variables turísticas con Deep Learning, Viedma, Daniel Trujillo, Rivera-Rivas A.J., Charte Francisco, and Díaz María J. del Jesu , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.939–943, (2018) PDF icon 2018-CAEPIA-TurismoLSTMs.pdf (127.66 KB)
Una estrategia difusa para la aplicación de operadores en un algoritmo evolutivo, Rivera-Rivas, A.J., Rojas I., J. Lopera Ortega, and del Jesus M. J. , XII Congreso Español sobre Tecnologías y Lógica Fuzzy(ESTYLF), September, Jaén, p.593-598, (2004)
Un sistema interactivo automático de aprendizaje y evaluación, Balsas, José R., Aguilera José, Vega Manuel García, and Rivas-Santos Victor M. , Congreso de innovación educativa en enseñanzas técnicas, 09, Donostia- San Sebastián (España), (2000)
Un sistema difuso evolutivo para la detección de excepciones en descubrimiento de subgrupos, Carmona, C. J., González P., and del Jesus M. J. , XV Conferencia de la Asociación Española para la Inteligencia Artificial, September, Madrid (Spain), p.1220-1229, (2013) PDF icon 2013 - LFSC.pdf (984.32 KB)
Un sistema de clasificación basado en reglas difusas jerárquico con programación genética para problemas de clasificación altamente no balanceados, López, Victoria, Fernández Alberto, del Jesus M. J., and Herrera F. , 02, (2012)
Un sistema coordinador de recursos distribuidos, López, Juan Antonio, Balsas José R., and Rivera-Rivas A.J. , Jornadas científicas en tecnologías de la información, 11, Cádiz (España), (2000)
Un Primer Estudio sobre la Utilización de Selección Evolutiva de Conjuntos de Entrenamiento en Problemas de Clasificación con Clases no Balanceadas y Árboles de Decisión, García, S., Fernández A., and Herrera F. , Proceedings of VI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, Málaga (Spain), p.183-190, (2009)
Un primer estudio sobre el uso de los sistemas de clasificación basados en reglas difusas en problemas de clasificación con clases no balanceadas, Fernández, A., García S., Herrera F., and del Jesus M. J. , Proceedings of the XIII Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Ciudad Real (Spain), p.89-95, (2006)
Un primer estudio sobre el uso de los sistemas de clasificación basados en reglas difusas en problemas de clasificación con clases no balanceadas, Fernández, Alberto, García Salvador, Herrera F., and del Jesus M. J. , XIV Congreso Español sobre tecnologías y lógica fuzzy, 01, Ciudad Real (Español), (2006)
Un estudio sobre el uso de algoritmos genéticos multimodales para selección de características, Aguilera, José, J J., Chica Manuel, del Jesus M. J., J M., Herrera F., and , 02, (2007)
Un algoritmo memético para la selección de prototipos: Una propuesta eficiente para problemas de tamaño medio, García, S., Cano J. R., and Herrera F. , Proceedings Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Tenerife, (2007)
Time Series forecasting: Automatic Determination of Lags and Radial Basis Neural Networks for a Changing Horizon Environment, Parras-Gutiérrez, E., and Rivas V. M. , 2010 IEEE World Congress on Computational Intelligence, July, Barcelona (Spain), p.4023-4029, (2010)
The Magina Project. The Renewables Potential for Electricity Production in the Province of Jaen, Southern Spain, Terrados, Julio, Ruiz-Arias Jose, Hontoria L, Almonacid G, Perez-Higueras Pedro, Pozo-Vazquez D, Gallego F.J., Gomez P, Castro Eulogio, Martin-Mesa A, et al. , 11, p.3452-3459, (2011)
The L-Co-R Co-evolutionary Algorithm: A Comparative Analysis in Medium-term Time-series Forecasting Problems, Parras-Gutiérrez, E., Rivas V. M., and Merelo Juan J. , International Joint Conference on Computational Intelligence (IJCCI), Vilamoura, Algarve (Portugal), p.144-151, (2013)
Tests de inclusión punto en objeto basados en árboles de intervalos, Martínez, Francisco, Rueda-Ruiz Antonio Jesús, and Feito-Higueruela Francisco Ramón , Congreso Español de Informática Gráfica, San Sebastián, p.57-64, (2009)
Symbpar vs Symbiotic_CHC_RBF: Diseñando redes de base radial de forma coevolutiva y paralela, García-Arenas, M., Parras-Gutiérrez E., and Rivas V. M. , VI Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, Málaga, p.231-238, (2009)
Supervising classrooms comprising children with dyslexia and other learning problems with graphical exploratory analysis for fuzzy data: Presentation of the software tool and case study, Palacios, Ana, and Sánchez Luciano , IEEE International Conference on Fuzzy Systems, 07, p.2133-2140, (2014)
Subgroup discovery in an e-learning usage study based on Moodle, Carmona, C. J., González P., del Jesus M. J., and Ventura S. , International Conference on EUropean Transnational Education (ICEUTE), October, Salamanca (Spain), p.26-31, (2011) PDF icon 2011 - ICEUTE.pdf (153.86 KB)
Subgroup Discovery Applied to the e-Commerce Website OrOliveSur.com, Carmona, C. J., Ramírez-Gallego S., Torres F., Bernal E., and del Jesus M. J. , 14th International Conference on Enterprise Information Systems (ICEIS), July, Wroclaw (Poland), p.239-244, (2012) PDF icon 2012 - ICEIS.pdf (1.85 MB)
Study of the Robustness of a Meta-Algorithm for the Estimation of Parameters in Artificial Neural Networks Design, Parras-Gutiérrez, E., del Jesus M. J., Rivas V. M., and Merelo Juan J. , Proceedings of the 2008 Eighth International Conference on Hybrid Intelligent Systems (HIS), September, Barcelona (Spain), p.519-524, (2008)
Statistical Comparisons by Means of Non-Parametric Tests: A Case Study on Genetic Based Machine Learning, García, S., Fernández A., Benítez A.D., and Herrera F. , Proceedings of the II Congreso Español de Informática (CEDI 2007). V Taller Nacional de Minería de Datos y Aprendizaje (TAMIDA), September, Zaragoza (Spain), p.95-104, (2007)
Some Results about Mutual Information-based Feature Selection and Fuzzy Discretization of Vague Data, Sánchez, L., Suarez M. R., Villar J. R., and Couso I. , 2007 IEEE International Fuzzy Systems Conference, July, p.1-6, (2007)
Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study, Charte, David, Sevillano-García Iván, Lucena-González María Jesús, Martín-Rodríguez José Luis, Charte Francisco, and Herrera Francisco , Hybrid Artificial Intelligent Systems, Cham, p.305–315, (2021)
Sistemas Basados en Reglas Difusas en Clasificación: Nuevos Retos, del Jesus, M. J. , XIV Congreso Español sobre tecnologías y lógica fuzzy, 09, Cuencas Mineras Asturianas (España), (2008)
Sistema de Clasificación con Reglas Difusas Utilizando Algoritmos Genéticos, Cordón, O., Díaz María José del, and Herrera F. , VI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF'96), Oviedo, (1996)
Simulating multi-self-similar spatiotemporal models with CUDA, Martínez, Francisco, Frías-Bustamante María Pilar, and Ruiz-Medina María Dolores , COMPSTAT 2010, París, del 22 al 27 de Agosto, p.341-341, (2010)
Simulación de fluidos dinámicos mediante autómatas celulares., Pérez-Godoy, M.D., Molina Andrés, and Pedro Sanchez , Congreso Español de informática gráfica., 06, Jaén, (1999)
Servicios de información sobre la EPSJ basados en entornos de publicación, Parras-Gutiérrez, E., Rivas V. M., and del Jesus M. J. , Free Libre Open Source Systems International Conference, March, Jerez de la Frontera (Cádiz), p.67-82, (2007)
Selecting the Most Informative Inputs in Modelling Problems with Vague Data Applied to the Search of Informative Code Metrics for Continuous Assessment in Computer Science Online Courses, Otero, José, Suárez Maria Del Rosari, Palacios Ana, Couso Inés, and Sánchez Luciano , Rough Sets and Current Trends in Computing, Cham, p.299–308, (2014)
Selecting Fuzzy-Ruled Based Classification System with Specific Reasoning Methods Using Genetical Algorithms, Cordón, O., Díaz María José del, and Herrera F. , Joint 9th IFSA World congres and 20th Nafips International, 07, Praga, (2001)
Selecting an Appropriate Statistical Test for Comparing Multiple Experiments in Evolutionary Machine Learning, Otero, José, Sánchez Luciano, and Alcala-Fdez Jesus , 09, (2007)
Selección Evolutiva de Instancias en Minería de Datos, Cano, J. R., Herrera F., and Lozano Manuel , Workwhop de Minería de Datos y Aprendizaje Automático, 01, Santander (España), (2002)
Scrae Web: Sistema de Corrección y Revisión Automática de Exámenes a Través de la Web, Pulido, Alfredo Sanchez, Cano J. R., and Pavón-Pulido Nieves , Jornadas de Enseñanza Universitaria de la Informática Jenui , 01, Cáceres (España), (2002)
RKEEL: Using KEEL in R code, Moyano, Jose, and Sánchez Luciano , 07, p.257-264, (2016)
ReturnOK: El pasado de la computación personal, García, Lina, Ruano Ildefonso, Charte Francisco, Molina Andrés, and Balsas José R. , V Congreso Internacional de Patrimonio e Historia de la Ingeniería, 4, Las Palmas de Gran Canaria (Spain), p.1–19, (2010) PDF icon 2010-CIPHI-Actas.pdf (1.16 MB)
Resampling Multilabel Datasets by Decoupling Highly Imbalanced Labels, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015, 6, Bilbao (Spain), p.489–501, (2015) PDF icon 2015-HAIS-REMEDIAL.pdf (1.04 MB)
Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms, Lozano, M., Herrera F., and Cano J. R. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
Reglas de asociación en datos multi-instancia mediante programación genética gramatical, Luna, J.M., Reyes O., del Jesus M. J., and Ventura S. , IX Simposio de Teoría y Aplicaciones de la Minería de Datos, 10, Granada, p.815-820, (2018)
Recognition of Activities in Resource Constrained Environments; Reducing the Computational Complexity, Espinilla, M., Rivera-Rivas A.J., Pérez-Godoy M.D., Medina J., Martínez L., and Nugent C. , Ubiquitous Computing and Ambient Intelligence, Cham, p.64–74, (2016)
R Ultimate Multilabel Dataset Repository, Charte, Francisco, Charte David, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.487–499, (2016) PDF icon RUMDR.pdf (294.87 KB)
QUINTA: A question tagging assistant to improve the answering ratio in electronic forums, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , IEEE International Conference on Computer as a Tool, EUROCON 2015, 9, Salamanca (Spain), p.1-6, (2015) PDF icon 2015-EUROCON-QUINTA.pdf (2.03 MB)
Programación de multicomputadoras basadas en objetos distribuidos, del Rio, Francisco Martínez, Pedro Sanchez, Capel-Tuñon Manuel Isidoro, and Balsas José R. , SEID99: Simposio español de informática distribuida, 02, Santiago de Compostela, (1999)
Presentación de TCL-TK para el desarrollo de aplicaciones por parte de usuarios no expertos en programación, González, P., Rivera-Rivas A.J., and Pérez-Godoy M.D. , Jornadas científicas andaluzas en tecnología de la información, Cádiz (España), (1998)
Preselection of Neurostimulation waveforms for visual prostheses using genetic algorithms, Romero, S., Guillén A., Carmona C. J., Morillas C., Pelayo F., and Pomares H. , 3rd International Conference on Biomedical Electronics and Devices (BIODEVICES), January, Valencia, p.191-194, (2010) PDF icon 2010 - BIODEVICES.pdf (232.28 KB)
Preprocessing vague imbalanced datasets and its use in genetic fuzzy classifiers, Palacios, A. M., Sánchez L., and Couso I. , International Conference on Fuzzy Systems, July, p.1-8, (2010)
Preliminary results on the application of boosting to learn weighted fuzzy rules under single-winner inference, Sánchez, Luciano, Otero José, and Suárez María , Congreso español de metaheurísticas, algoritmos evolutivos y bioinspirados., Córdoba-España, (2004)
Predicción de tráfico mediante co-evolución de Redes Neuronales de Funciones de Base Radial y selección de variables de entrada, Rivas, V. M., Parras-Gutiérrez E., Arenas M.G., Castillo P.A., Garcia-Sanchez P., Merelo Juan J., and Garcia-Fernandez P. , Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Madrid (Spain), p.782-791, (2013)
Predicción de series temporales mediante la coevolución de funciones base, Rivera-Rivas, A.J., Rojas I., and J. Lopera Ortega , Tercer Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados MAEB, February, p.585-592, (2004)
Predicción de Series Temporales a largo plazo mediante Algoritmos Meta-evolutivos y Redes Neuronales de Funciones Base Radial, Parras-Gutiérrez, E., Rivas V. M., Olmo M. J., Fernandez-Montoya A., and Cillero M. , III Simposio de Inteligencia Computacional (SICO), September, Valencia, p.49-56, (2010)
Predicción a muy corto plazo de series temporales de volumen de tráfico rodado mediante co-evolución de RNFBR, Rivas, V. M., Parras-Gutiérrez E., Fernandez-Ares a., Castillo P.A., Garcia-Fernandez P., and Arenas M.G. , Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Mérida - Almendralejo (Spain), p.181-188, (2015)
Potenciando el aprendizaje proactivo con ILIAS&WebQuest: aprendiendo a paralelizar algoritmos con GPUs, Santamaría, J, Espinilla Macarena, Rivas Antonio Rivera, and Romero Samuel , Jornadas de enseñanza universitaria de la informática, 01, Santiago de Compostela (España), (2010)
Parameter Estimation for Radial Basis Function Neural Network Design by Means of Two Symbiotic Algorithms, Parras-Gutiérrez, E., Rivas V. M., del Jesus M. J., and Merelo Juan J. , Proceedings of the 2008 The Second International Conference on Advanced Engineering Computing and Applications in Sciences (ADVCOMP), September, Valencia (Spain), p.164-169, (2008)
Parallelizing the Design of Radial Basis Function Neural Networks by Means of Evolutionary Meta-algorithms, Arenas, M.G., Parras-Gutiérrez E., Rivas V. M., Castillo P.A., del Jesus M. J., and Merelo Juan J. , International Work-Conference on Artificial Neural Networks (IWANN), June, Salamanca (Spain), p.383-390, (2009)
Optimizing Supply Strategies in the Spanish Electrical Market., Marín, Enrique, and Sánchez Luciano , 06, Volume 2687, p.353-360, (2003)
Optimizing RBF Networks with Cooperative/Competitive Evolution of Units and Fuzzy Rules, Rivas, Antonio Rivera, Ortega Julio, Rojas Ignacio, and Prieto Alberto , 06, p.570-578, (2001)
Optimización genético borrosa de parámetros en un sistema de bajo coste para la medición visual de cotas de vehículos, Otero, José, Otero Adolfo, Junco Luis, and Sánchez Luciano , Congreso Español sobre tecnologías y lógica fuzzy, 01, León (España), (2002)
Optimización de redes de RBFs mediante cooperación-competición de neuronas y algoritmos de minimización de error, Rivera-Rivas, A.J., Rojas I., J. Lopera Ortega, and del Jesus M. J. , MAEB, February, p.499-508, (2003)
Online SOC estimation of Li-FePO4 batteries through an observer of the system state with minimal nonspecificity, Sánchez, Luciano, Couso Inés, and Blanco Cecilio , 08, p.1-8, (2015)
On the Use of Bagging, Mutual Information-Based Feature Selection and Multicriteria Genetic Algorithms to Design Fuzzy Rule-Based Classification Ensembles, Cordón, O., Quirin A., and Sánchez L. , 2008 Eighth International Conference on Hybrid Intelligent Systems, Sep., p.549-554, (2008)
On the Impact of Imbalanced Data in Convolutional Neural Networks Performance, Pulgar-Rubio, F., Rivera-Rivas A.J., Charte Francisco, and del Jesus M. J. , 12th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2017, 6, La Rioja (Spain), p.220–232, (2017) PDF icon Pulgar2017_Chapter_OnTheImpactOfImbalancedDataInC.pdf (634.69 KB)
On the Impact of Dataset Complexity and Sampling Strategy in Multilabel Classifiers Performance, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 11th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2016, 4, Seville (Spain), p.500–511, (2016) PDF icon Complexity.pdf (1.56 MB)
Obtención de Sistemas Basados en Reglas Difusas Precisos y Compactos Mediante Algoritmos Genéticos Multiobjetivo, Alcalá, R., Alcalá-Fdez J., and Gacto M. J. , Proceedings of the XIII Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), p.1-6, (2006)
Obtaining Compact and Still Accurate Linguistic Fuzzy Rule-Based Systems by Using Multi-Objetive Genetic Algorithms, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the Symposium on Fuzzy Systems in Computer Science (FSCS), p.53-62, (2006)
Obtaining accurate TSK Fuzzy Rule-Based Systems by Multi-Objective Evolutionary Learning in high-dimensional regression problems, Gacto, M. J., Galende M., Alcalá R., and Herrera F. , IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 07/2013, p.1-7, (2013) PDF icon 2013-MJGacto.pdf (364.78 KB)
Objetos distribuidos versus paso de mensajes como soporte para la representación de abstracciones distribuidas, del Rio, Francisco Martínez, Balsas José R., Rivas Victor M., and Capel-Tuñon Manuel Isidoro , Simposio Español de informática distribuida, 09, Orense (España), (2000)
Nuevos métodos de razonamiento en sistemas de clasificación basados en reglas difusas, Cordón, O., Díaz María José del, and Herrera F. , Congreso español sobre tecnologías y lógica fuzzy., Tarragona, (1997)
Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup Discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , Proceedings of the Fourth International Conference on Hybrid Artificial Intelligence Systems (HAIS), June, Volume 5572, Salamanca (Spain), p.573-580, (2009) PDF icon 2009 - HAIS.pdf (166.16 KB)
Niching genetic feature selection algorithms applied to the design of fuzzy rule-based classification systems, Aguilera, José, Chica M., del Jesus M. J., and Herrera F. , 2007 IEEE International Fuzzy Systems Conference, July, p.1-6, (2007)
Mutual Information-Based Feature Selection in Fuzzy Databases Applied to Searching for the Best Code Metrics in Automatic Grading, Otero, José, Suárez Rosario, and Sánchez Luciano , Hybrid Artificial Intelligence Systems, Cham, p.330–341, (2014)
Multi-Objective Genetic Fuzzy Systems: On the Necessity of Including Expert Knowledge in the MOEA Design Process, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, p.1446-1453, (2008)
Multiobjective genetic algorithm for extractiong subgroup discovery fuzzy rules, González, P., del Jesus M. J., and Herrera F. , 2007 IEEE Symposium on Computational Intelligence in Multicriteria Decision Making (IEEE MCDM), Honolulu (USA), p.50-57, (2007)
Multiobjective evolutionary induction of subgroup discovery rules in a market problem, Berlanga, F. J., del Jesus M. J., González P., and Herrera F. , 2nd International Conference on Machine Intelligence (ACIDCA-ICMI), Tozeur (Tunisia), p.610-617, (2005)
Multiobjective Evolutionary Induction of Subgroup Discovery Fuzzy Rules: A Case Study in Marketing, Berlanga, F. J., del Jesus M. J., González P., Herrera F., and Mesonero M. , 6th Industrial Conference on Data Mining (ICDM), Volume 4065, Leipzig (Germany), p.337-349, (2006)
Multi-label Testing for CO2RBFN: A First Approach to the Problem Transformation Methodology for Multi-label Classification, Rivera-Rivas, A.J., Charte Francisco, Pérez-Godoy M.D., and del Jesus M. J. , 11th International Work-Conference on Artificial Neural Networks, IWANN 2011, 6, Torremolinos-Málaga (Spain), p.41–48, (2011) PDF icon 2011-IWANN-MultilabelTestingCO2RBFN.pdf (131.76 KB)
Multi-class Imbalanced Data-Sets with Linguistic Fuzzy Rule Based Classification Systems Based on Pairwise Learning, Fernández, A., del Jesus M. J., and Herrera F. , 13th International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, Volume 6178, Dortmund (Germany), p.89-98, (2010)
MOEA-EFEP: Un algoritmo evolutivo multi-objetivo para la extracción de patrones emergentes difusos, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.671-672, (2018) PDF icon 2018_Garcia_MAEB.pdf (67.49 KB)
Modelos Evolutivos de Extracción de Conocimiento en Aplicaciones Médicas: Enfermedad de Parkinson y Urgencias PSiquiátricas, Aguilera, José, Díaz María José del, González P., Herrera F., Navío M., and Saiz J. , Workshop de Minería de Datos y Aprendizaje Automático, 01, Santander (España), (2002)
Modelos descriptivos basados en aprendizaje supervisado para el tratamiento de grandes volúmenes de datos y flujos continuos de datos, García-Vico, A.M. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.1402-1407, (2018) PDF icon 2018_Garcia_DocConsCAEPIA.pdf (114.01 KB)
Modelo gráfico de transporte de agua a través del estrecho de Gibraltar a partir de imágenes de satelites, Molina-Aguilar, Andrés, and Aguilera José , Jornadas de análisis de variables y simulación numérica del intercambio de masas de agua a través del estrecho de Gibraltar, 06, Cádiz (España), (2000)
Modeling Vague Data with Genetic Fuzzy Systems under a Combination of Crisp and Imprecise Criteria, Sánchez, L., Couso I., and Casillas J. , 2007 IEEE Symposium on Computational Intelligence in Multi-Criteria Decision-Making, April, p.30-37, (2007)
Modeling the Transformation of Olive Tree Biomass into Bioethanol with Reg-CO2RBFN, Charte, Francisco, Romero Inmaculada, Rivera-Rivas A.J., and Castro Eulogio , 14th International Work-Conference on Artificial Neural Networks (IWANN 2017), 6, Cádiz (Spain), p.733–744, (2017) PDF icon 2017IWANN-Biomass.pdf (158.82 KB)
MLSMOTE: Approaching imbalanced multilabel learning through synthetic instance generation, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.821–822, (2016) PDF icon 2016-CAEPIA-MLSMOTE.pdf (579.04 KB)
MLeNN: A First Approach to Heuristic Multilabel Undersampling, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 15th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2014, 9, Salamanca (Spain), p.1-9, (2014) PDF icon 2014-IDEAL-MLeNN.pdf (184.04 KB)
mldr: Paquete R para Exploración de Datos Multietiqueta, Charte, David, and Charte Francisco , XVI Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2015), 11, Albacete (Spain), p.695–704, (2015) PDF icon 2015-CAEPIA-mldr.pdf (2.39 MB)
Mining association rules in R using the package RKEEL, Sánchez, O., Moyano J. M., Sánchez L., and Alcála-Fádez J. , 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, p.1-6, (2017)
Minería de Patrones Emergentes: Una oportunidad para la extracción evolutiva de conocimiento, García-Vico, A.M., Carmona C. J., González P., and del Jesus M. J. , XI Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2016), (2016) PDF icon 2016-Garcia-EPMReview.pdf (240.75 KB)
Métodos de razonamiento aproximado basados en el concepto de mayoría difusa para sistemas de clasificación, Cordón, O., Díaz María José del, and Herrera F. , Congreso español sobre tecnología y lógica fuzzy, 09, Pamplona (España), (1998)
Mejoras en el Diseño Multiobjetivo de Redes de Funciones de Base Radial, López, P.L., Rivera-Rivas A.J., Carmona C. J., and Pérez-Godoy M.D. , Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), p.441-446, (2010) PDF icon 2010 - ESTYLF.pdf (587.96 KB)
Managing stochastic algorithms cross-validation variability using an interval valued multiple comparison procedure, Otero, José, Sánchez Luciano, Palacios Ana, and Couso Inés , International Conference on Intelligent Systems Design and Applications, 11, p.1391-1396, (2011)
Managing imprecisely observed data in Genetic Fuzzy Models by means of a fuzzy-valued fitness function, Sánchez, Luciano, and Couso Inés , Congreso español de metaheurísticas, algoritmos evolutivos y bioinspirados., 01, Granada (España), (2005)
Learning fuzzy rules using genetic programming: Context-free grammar definition for high-dimensionality problems, Berlanga, F. J., del Jesus M. J., and Herrera F. , I International Workshop on Genetic Fuzzy Systems (GFS), Granada (Spain), p.136-141, (2005)
Learning Fuzzy Linguistic Models from Low Quality Data by Genetic Algorithms, Sánchez, L., and Otero J. , 2007 IEEE International Fuzzy Systems Conference, July, p.1-6, (2007)
Learning compact fuzzy rule-based classification systems with genetic programming, Berlanga, F. J., del Jesus M. J., and Herrera F. , 4th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), Barcelona (Spain), p.1027-1032, (2005)
Layer-based Decompositions of Polyhedra, Rueda, Antonio, Martínez Francisco, and Feito Francisco , International Conference in Central Europe on Computer Graphics Visualization and Computer Vision, January, (2005)
La descomposición multi-L-REP de sólidos y su aplicación a un test de inclusión, Martínez, Francisco, and Rueda-Ruiz Antonio Jesús , XVII Congreso Español de Informática Gráfica, Zaragoza, del 11 al 14 de Septiembre, p.159-168, (2007)
La asignatura de planificación de sistemas informáticos en ingeniería técnica en informática de gestión., González, P., Pérez-Godoy M.D., and Rivera-Rivas A.J. , Jenui, 01, Alcala de Henares (España), (2000)
Knowledge Extraction from Fuzzy Data for Estimating Consumer Behavior Models, Casillas, J., and Sánchez L. , 2006 IEEE International Conference on Fuzzy Systems, July, p.164-170, (2006)
KEEL: A Data Mining Software Tool Integrating Genetic Fuzzy Systems, Alcalá-Fdez, J., García S., Berlanga F. J., Fernández A., Sánchez L., del Jesus M. J., and Herrera F. , 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS), WittenBommerholz (Germany), p.83-88, (2008)
JavaScript como lenguaje de apoyo a la docencia vía web, Rivas, Victor M., Balsas José R., Aguilera José, and Lopez L.Alfonso Ureña , Jornadas de la enseñanza universitaria Jenui, 07, Palma de Mallorca (España), (2001)
Introducing a genetic fuzzy linguistic combination method for bagging fuzzy rule-based multiclassification systems, Sánchez, L., Cordón O., Quirin A., and Trawinski K. , 2010 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), March, p.75-80, (2010)
Intelligent Systems in Long-Term Forecasting of the Extra-Virgin Olive Oil Price in the Spanish Market, Pérez-Godoy, M.D., Pérez Pedro, Rivera-Rivas A.J., del Jesus M. J., Frías María Pilar, and Parras Manuel , Trends in Applied Intelligent Systems, Berlin, Heidelberg, p.205–214, (2010)
IN-RECS: Índice de Impacto de las Revistas Españolas de Ciencias Sociales, Jiménez, E., Delgado E., Ruiz-Baños R., López-Herrera A.G., Gacto M. J., Torres D., Moneda M., Ruiz-Baños R., Pérez J.M., Bailón R., et al. , Proceedings of the IX Jornadas Españolas de Documentación, (2005)
Influencia del uso de modificadores lingüísticos y grados de certeza en un sistema de clasificación basados en reglas difusas, del Jesus, M. J., and Herrera F. , X Congreso Español sobre tecnologías y reglas difusas, 09, Santander (España), (2000)
Influencia de la granularidad y de las medidas de calidad en SDIGA, González, P., Carmona C. J., del Jesus M. J., and Herrera F. , XIV Congreso Español de Tecnologías y Lógica Difusa( ESTYLF), September, Langreo-Mieres (Spain), (2008) PDF icon 2008b - ESTYLF.pdf (338.36 KB)
Inducción evolutiva multiobjetivo de reglas de descripción de subgrupos en un problema de marketing, del Jesus, M. J., González P., and Herrera F. , IV Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Granada (Spain), p.661-669, (2005)
Indice de Interpretabilidad Semántica para el Ajuste de Sistemas Basados en Reglas Difusas y Selección de Reglas Mediante un Algoritmo Evolutivo Multi-Objetivo, Gacto, M. J., Alcalá R., and Herrera F. , XV Edición del Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), February, Huelva, p.73-78, (2010)
Incorporating Knowledge in Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1358-1366, (2006)
Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-sets Using an Evolutionary Adaptive Inference System, Fernández, A., del Jesus M. J., and Herrera F. , 10th International Work-Conference on Artificial Neural Networks (IWANN), June, Volume 5517, Salamanca (Spain), p.294-301,, (2009)
Improving Multi-label Classifiers via Label Reduction with Association Rules, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 7th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2012), 9, Salamanca (Spain), p.188–199, (2012) PDF icon 2012-HAIS-LabelReduction.pdf (171.47 KB)
Improving Fuzzy Rule-Based Decision Models by Means of a Genetic 2-Tuples Based Tuning and the Rule Selection, Alcalá, R., Alcalá-Fdez J., Berlanga F. J., Gacto M. J., and Herrera F. , Modeling Decisions for Artificial Intelligence (MDAI), Volume 3885, Tarragona (Spain), p.317-328, (2006)
Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism, González-Almagro, Germán, Rosales-Pérez Alejandro, Luengo Julián, Cano J. R., and García Salvador , GECCO '20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 06/2020, p.333–341, (2020) PDF icon 3377930.3390187.pdf (297.15 KB)
Implementation of Data Stream Classification Neural Network Models Over Big Data Platforms, Puentes, F., Pérez-Godoy M.D., González P., and del Jesus M. J. , International Work-Conference on Artificial Neural Networks (IWANN 2021), p.272–280, (2021)
Impact of the Type of Rule in Fuzzy Emerging Pattern Mining on a Big Data Approach, García-Vico, A.M., González P., Carmona C. J., and del Jesus M. J. , Proc. of the II International symposium on Fuzzy and Rough Sets (ISFUROS 2017), (2017) PDF icon 2017-Garcia-ISFUROS.pdf (317.55 KB)
Hibridación de métodos filtro y de envoltura para selección de características, García, Jose Joaquin Ag, Díaz María José del, and Herrera F. , Conferencia de la asociación Española para la inteligencia artificial. III Jornada de transferencia tecnológica de inteligencia artificial., 01, Murcia (España), (1999)
Herramientas para el desarrollo de prácticas en una asignatura de redes de computadores de una ingeniería técnica, Rivera-Rivas, A.J., and Pérez-Godoy M.D. , Jornadas de informática, Cádiz (España), (1997)
Handling High-Dimensional Regression Problems by Means of an Efficient Multi-Objective Evolutionary Algorithm, Gacto, M. J., Alcalá R., and Herrera F. , 9th International Conference on Intelligent Systems Design and Applications (ISDA), November, Pisa (Italy), p.109-114, (2009)
Graph Based GP Applied to Dynamical Systems Modeling, Lopez, Antonio, García Hilario López, and Sánchez Luciano , 06, Volume 2084, p.725-732, (2001)
GFS-Based Analysis of Vague Databases in High Performance Athletics, Palacios, Ana, Couso Inés, and Sánchez Luciano , 09, p.602-609, (2009)
Genetic tuning of fuzzy rule-based systems integrating linguistic hedges, Casillas, J., Cordón O., Herrera F., and del Jesus M. J. , Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), July, Volume 3, p.1570-1574 vol.3, (2001)
Genetic Search of Block-Based Structures of Dynamical Process Models, Lopez, Antonio, and Sánchez Luciano , 06, Volume 2686, p.526-533, (2003)
Genetic Learning of Membership Functions for Mining Fuzzy Association Rules, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the 16th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, London (United Kingdom), p.1538-1543, (2007)
Genetic Lateral and Amplitude Tuning with Rule Selection for Fuzzy Control of Heating, Ventilating and Air Conditioning Systems, Alcalá, R., Alcalá-Fdez J., Berlanga F. J., Gacto M. J., and Herrera F. , 19th International Conference on Industrial & Engineering Applications of Artificial Intelligence & Expert Systems (IEA/AIE), Volume 4031, Annecy (France), p.452-461, (2006)
Genetic Lateral and Amplitude Tuning of Membership Functions for Fuzzy Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Proceedings of the 2nd International Conference on Machine Intelligence (ACIDCA-ICMI), p.589-595, (2005)
Genetic Fuzzy Modelling of Li-Ion Batteries Through a Combination of Theta-DEA and Knowledge-Based Preference Ordering, Echevarría, Yuviny, Sánchez Luciano, and Blanco Cecilio , Advances in Artificial Intelligence, Cham, p.310–320, (2016)
Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets, Fernández, A., Berlanga F. J., del Jesus M. J., and Herrera F. , 13 th International Fuzzy Systems Association World Congress and 6th European Society for Fuzzy Logic and Tecnology Conference (IFSA-EUSFLAT), Lisbon (Portugal), p.42-47, (2009)
Genetic Algorithms for Estimating Longest Path from Inherently Fuzzy Data Acquired with GPS, Villar, José, Otero Adolfo, Otero José, and Sánchez Luciano , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning, Berlin, Heidelberg, p.232–240, (2006)
Generalized stochastic orderings applied to the study of perfomance of machine learning algorithm, Couso, Inés, and Sánchez Luciano , The 16th World Congress of the International Fuzzy Systems Association (IFSA) and the 9th Conference of the European Society for Fuzzy Logic and Technology (EUSFLAT), 06, Gijón, Asturias(Spain), (2015)
Gamificación mediante juegos de bloques en asignaturas del ámbito de la Inteligencia Artificial en el Grado en Ingeniería Informática, Carmona, C. J., González P., and García-Vico A.M. , VI Congreso Internacional sobre Innovación Pedagógica y Praxis Educativa (INNOVAGOGÍA 2022) - 25 al 27 de mayo, Madrid, (2022)
FuGePSD: Fuzzy Genetic Programming-based algorithm for Subgroup Discovery, Carmona, C. J., González P., and del Jesus M. J. , 16th World Congress of the International Fuzzy Systems Association and 9th Conference of the European Society for Fuzzy Logic and Technology, p.1-8, (2015) PDF icon 2015 - IFSA-EUSFLAT - CoreB.pdf (889.5 KB)
FEPDS: Una propuesta para la extracción de patrones emergentes difusos en flujos continuos de datos, García-Vico, A.M., Seker H., Carmona C. J., González P., and del Jesus M. J. , Proceedings of the XIX Conference of the Spanish Association for Artificial Intelligence, (2021) PDF icon 2021 - CAEPIA - FEPDS.pdf (173.43 KB)
Feature Selection Algorithms Applied to Parkinson's Disease, Navío, M., Aguilera José, del Jesus M. J., González R., Herrera F., and Iríbar C. , Medical Data Analysis, Berlin, Heidelberg, p.195–200, (2001)
Extracción Evolutiva de Reglas de Asociación en un Servicio de Urgencias Psiquiátricas, Aguilera, J., del Jesus M. J., González P., Herrera F., Navío M., and Sáinz J. , II Congreso español sobre Metaheurísticas, Algoritmos evolutivos y bioinspirados(MAEB), Gijón(Spain), p.548-555, (2003)
Extracción de reglas DNF difusas en un problema de marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , XII Congreso Español de Tecnologías y Lógica Difusa(ESTYLF), Jaén (Spain), p.351-356, (2004)
Experimentando con la paralelización de un problema de cálculo utilizando hardware gráfico, Martínez, Francisco, Rueda-Ruiz Antonio Jesús, Feito-Higueruela Francisco Ramón, and Frías-Bustamante María Pilar , XVIII Jornadas de Paralelismo, Zaragoza, del 11 al 14 de Septiembre, p.791-798, (2007)
Evolving Fuzzy Rule Based Classifiers with GA-P: A Grammatical Approach, Carbajal, Santiago, Martinez Fermín González, and Sánchez Luciano , 05, Volume 1598, p.203-210, (1999)
Evolutionary Multi-Objective Algorithm to Effectively Improve the Performance of the Classic Tuning of Fuzzy Logic Controllers for a Heating, Ventilating and Air Conditioning System, Gacto, M. J., Alcalá R., and Herrera F. , 5th International Workshop On Genetic And Evolutionary Fuzzy Systems (GEFS), April, (2011)
Evolutionary approaches to the learning of fuzzy rule-based classification systems, Cordón, O., Herrera F., and del Jesus M. J. , (1999)
Evolutionary algorithms for subgroup discovery applied to e-learning data, Carmona, C. J., González P., del Jesus M. J., Romero C., and Ventura S. , IEEE EDUCON, April, Madrid (Spain), p.983-990, (2010) PDF icon 2010 - IEEEEDUCON.pdf (125.61 KB)
Evolución de la asignatura metodología y tecnología de la programación, Aguilera, José, Balsas José R., and Díaz María José del , Jenui, 01, Alcalá de Henares (España), (2000)
E-tsRBF: preliminary results on the simultaneous determination of time-lags and parameters of Radial Basis Function Neural Networks for time series forecasting, Parras-Gutiérrez, E., Rivas V. M., and del Jesus M. J. , 9th International Conference on Intelligent Systems Design and Applications, December, Pisa (Italy), p.1445-1449, (2009)
E-tsRBF: Automatic determination of lags to forecast time series by means of Radial Basis Function Neural Networks, Parras-Gutiérrez, E., and Rivas V. M. , I International Workshop on Mining of Non-Conventional Data (MINCODA), November, Sevilla (Spain), p.42-49, (2009)
Estudio de las Fases de un Algoritmo de Optimización para Redes de Funciones de Base Radial, Rivera-Rivas, A.J., Rojas I., and J. Lopera Ortega , Actas del Simposio de Inteligencia Computacional (SICO), September, Granada. Spain, p.237-244, (2005)
Estudio de la influencia de las medidas de complejidad de los datos en los Sistemas de Clasifcación Basados en Reglas Difusas: Análisis de la Razón Discriminante de Fisher, Luengo, J., García S., Cano J. R., and Herrera F. , XIV Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), September, Mieres (Spain), p.257-263, (2008)
Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach, Carmona, C. J., Pulgar-Rubio F., Rivera-Rivas A.J., del Jesus M. J., and Aguilera J. , Proceedings of the Eleventh International Conference on Hybrid Artificial Intelligence Systems (HAIS), April, Sevilla (Spain), p.273-282, (2016) PDF icon 2016 - HAIS - CoreC.pdf (203.25 KB)
Estimación de la Longitud de Línea de Baja Tensión Mediante Técnicas Evolutivas de Análisis de Datos, Cordón, O., Spín Antonio, Fajardo Waldo, Herrera F., and Sánchez Luciano , 8ª Reunión Nacional de Grupos de Investigación en Ingeniería Eléctrica, (1998)
Enhanced Radial Basis Function Neural Network Design Using Parallel Evolutionary Algorithms, Parras-Gutiérrez, E., García-Arenas M., and Rivas V. M. , 11th International Conference on Engineering Applications of Neural Networks (EANN), August, London, p.269-280, (2009)
Engine Health Monitoring for engine fleets using fuzzy radviz, Martínez, A., Sánchez L., and Couso I. , 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, p.1-8, (2013)
Energy-Efficient Sound Environment Classifier for Hearing Aids Based on Multi-objective Simulated Annealing Programming, Cocaña-Fernández, Alberto, Sánchez Luciano, Ranilla José, Gil-Pita Roberto, and Ayllón David , 10th International Conference on Soft Computing Models in Industrial and Environmental Applications, Cham, p.261–270, (2015)
EMORBFN: An Evolutionary Multiobjetive Optimization Algorithm for RBFN Design, López, P.L., Rivera-Rivas A.J., Pérez-Godoy M.D., del Jesus M. J., and Carmona C. J. , International Work-Conference on Artificial Neural Networks (IWANN), Number 2009, p.752–759, (2009) PDF icon 2009 - IWANN - CoreB.pdf (190.56 KB)
E2PAMEA: un algoritmo evolutivo para la extraccióni eficiente de patrones emergentes difusos en entornos big data, García-Vico, A.M., Elizondo D., Charte Francisco, González P., and Carmona C. J. , Proceedings of the XIX Conference of the Spanish Association for Artificial Intelligence, (2021) PDF icon 2021 - CAEPIA - E2PM.pdf (173.29 KB)
Designing Radial Basis Function Neural Networks with Meta-Evolutionary Algorithms: The Effect of Chromosome Codification, Parras-Gutiérrez, E., Rivas V. M., del Jesus M. J., and Merelo Juan J. , International Work-Conference on Artificial Neural Networks (IWANN), June, Salamanca (Spain), p.37-40, (2009)
Descubrimiento de subgrupos mediante sistemas difusos evolutivos, Carmona, C. J. , II Jornadas Andaluzas de Informática (JAI), September, Canillas del Aceituno (Spain), p.30-35, (2011) PDF icon 2011 - JAI.pdf (2.11 MB)
Defuzzification of Fuzzy p-Values, Couso, Inés, and Sánchez Luciano , Soft Methods for Handling Variability and Imprecision, Berlin, Heidelberg, p.126–132, (2008)
Credal C4.5 with Refinement of Parameters, Mantas, Carlos J., Abellán Joaquín, Castellano Javier G., Cano J. R., and Moral Serafín , Information Processing and Management of Uncertainty in Knowledge-Based Systems. Applications, Cham, p.739–747, (2018)
Cost Sensitive and Preprocessing for Classification with Imbalanced Data-sets: Similar Behaviour and Potential Hybridizations, López, Victoria, Fernández Alberto, del Jesus M. J., and Herrera F. , ICPRAM 2012 - Proceedings of the 1st International Conference on Pattern Recognition Applications and Methods, 02, Volume 2, (2012)
Concurrence among Imbalanced Labels and Its Influence on Multilabel Resampling Algorithms, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 9th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2014), 6, Salamanca (Spain), p.110–121, (2014) PDF icon 2014-HAIS-ConcurrenceLabels.pdf (1.12 MB)
Computing the spanish medium electrical line maintenance costs by means of evolution-based learning processes, Cordón, O., Herrera F., and Sánchez Luciano , Methodology and Tools in Knowledge-Based Systems, Berlin, Heidelberg, p.478–486, (1998)
Combining simple exponential smoothing models for time series forecasting, Martínez, Francisco, Pérez-Godoy M.D., Charte Francisco, and del Jesus M. J. , International work-conference on Time Series, ITISE 2016, 6, Granada (Spain), p.635-644, (2016) PDF icon 2016-ITISE-ExponentialSmoothing.pdf (1.13 MB)
Combination of self-organizing maps and multilayer perceptrons for speaker independent isolated word recognition, Tuya, J., Arias E., Sánchez L., and Corrales J. A. , New Trends in Neural Computation, Berlin, Heidelberg, p.550–555, (1993)
CoEvRBFN: An Approach to Solving the Classification Problem with a Hybrid Cooperative-Coevolutive Algorithm, Pérez-Godoy, M.D., Rivas Antonio Rivera, del Jesus M. J., and Rojas Ignacio , 06, p.324-332, (2007)
Co-Evolutionary Algorithm for RBF by Self- Organizing Population of neurons, Rivas, Antonio Rivera, Ortega Julio, Rojas Ignacio, and del Jesus M. J. , 06, Volume 2686, p.470-477, (2003)
CO2RBFN-CS: First Approach Introducing Cost-Sensitivity in the Cooperative-Competitive RBFN Design, Pérez-Godoy, M.D., Rivera-Rivas A.J., Charte Francisco, and del Jesus M. J. , 13th International Work-Conference on Artificial Neural Networks (IWANN 2015), 6, Palma de Mallorca (Spain), p.361–373, (2015)
Clustering: Un paquete R para facilitar el análisis de algoritmos de agrupamiento, Pérez-Martos, L.A., González P., and Carmona C. J. , Proceedings of the XIX Conference of the Spanish Association for Artificial Intelligence, (2021) PDF icon 2021 - CAEPIA - Clustering.pdf (484.99 KB)
CI-LQD: A software tool for modeling and decision making with Low Quality Data, Palacios, A. M., Sánchez L., and Couso I. , 2013 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, p.1-8, (2013)
Boosting of fuzzy models for high-dimensional imprecise datasets, Sánchez, Luciano, and Ramón José , Information Processing and Management of Uncertainty in Knowledge-Based Systems, 07, París (Francia), (2006)
Battery diagnosis for electrical vehicles through semi-physical fuzzy models, Sánchez, L., Otero J., Couso I., and Blanco C. , 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, p.416-423, (2016)
Automating Autoencoder Architecture Configuration: An Evolutionary Approach, Charte, Francisco, Rivera-Rivas A.J., Martínez Francisco, and del Jesus M. J. , International Work-Conference on the Interplay Between Natural and Artificial Computation, 05/2019, p.339-349, (2019)
Automatic Time Series Forecasting with GRNN: A Comparison with Other Models, Martínez, Francisco, Charte Francisco, Rivera-Rivas A.J., and Frías María Pilar , International Work-Conference on Artificial Neural Networks, 05/2019, p.198-209, (2019)
Automatic Neural Net Design by Means of a Symbiotic Co-evolutionary Algorithm, Parras-Gutiérrez, E., Rivas V. M., and del Jesus M. J. , HAIS 2008: 3rd International Workshop on Hybrid Artificial Intelligence System, October, p.140-147, (2008)
Atipicidad: Medida de calidad clave dentro del descubrimiento de reglas descriptivas supervisadas, Carmona, C. J., del Jesus M. J., and Herrera F. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.827-828, (2018) PDF icon 2018 - CAEPIA-70.pdf (67.19 KB)
Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model, Echevarría, Yuviny, Sánchez Luciano, and Blanco Cecilio , Hybrid Artificial Intelligent Systems, Cham, p.250–260, (2016)
Assessing the evolution of learning capabilities and disorders with graphical exploratory analysis of surveys containing missing and conflicting answers, Sánchez, Luciano, Couso Inés, Otero José Varela, and Palacios Ana M. , (2010)
Aproximaciones de Evolución con Funciones Difusas Mediante Cooperacion y Competición de RBFs, Rivera-Rivas, A.J., Ortega Julio, Díaz María José del, and González-Peñalvez Jesús , Congreso Español de Algoritmos Evolutivos y Bioinspirados AEB-02, 01, Mérida, (España), (2002)
Aprendizaje jerárquico por refuerzo mediante programación genética dirigida por gramáticas, Carbajal, Santiago, and Sánchez Luciano , Congreso Español de algoritmos evolutivos y bioinspirados AEB-02, 01, Mérida (España), (2002)
Aprendizaje Evolutivo De Sistemas Aproximativos De Tipo TSK Para Problemas De Alta Dimensionalidad, Gacto, M. J., Alcalá R., and Herrera F. , XVI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), February, Valladolid (Spain), p.295-300, (2012)
Aprendizaje Evolutivo de los Contextos de las Funciones de Pertenencia para Extraer Reglas de Asociación Difusas, Alcalá-Fdez, J., Alcalá R., Gacto M. J., and Herrera F. , Proceedings of the II Congreso Español de Informática (CEDI 2007). II Simposio sobre Lógica Fuzzy y Soft Computing (LFSC), September, p.25-32, (2007)
Aprendizaje de reglas difusas mediante programación genética en problemas con alta dimensionalidad, Berlanga, F. J., del Jesus M. J., and Herrera F. , I Simposio sobre Lógica Fuzzy y Soft Computing (LFSC), Granada (Spain), p.93-100, (2005)
Approximating The Discrete Space Equation From Chaotic Noisy Data, Fernández, A., Sánchez Luciano, and Navarro J.J. , International Conference On Information Processing and Management Of Uncertainty In Knowledge-Based System, 01, (2000)
Applied Techniques of Engineering to Non-Structured Data Model, Carmona, C. J., del Jesus M. J., Guerrero P., Peña-Santiago R., and Rivas V. M. , International Symposium on Distributed Computing and Artificial Intelligence (DCAI), Volume 50, Salamanca (Spain), p.410-414, (2008) PDF icon 2008 - DCAI.pdf (246.2 KB)
Application of ANOVA to a Cooperative-Coevolutionary Optimization of RBFNs, Rivas, Antonio Rivera, Rojas Ignacio, and Ortega Julio , Lecture Notes in Computer Science, 06, Volume 3512, p.297-305, (2005)
Aportaciones de la ingeniería de la programación al curriculum del ingeniero técnico industrial, Balsas, José R., and Aguilera José , Jornadas sobre la enseñanza universitaria de la informática, 09, Alcalá de Henares (España), (2000)
Aplicación de un algoritmo de extracción de reglas difusas para minería de uso web, Carmona, C. J., González P., Rivas V. M., and del Jesus M. J. , XIV Congreso Español de Tecnologías y Lógica Difusa (ESTYLF), September, Langreo-Mieres (Spain), (2008) PDF icon 2008a - ESTYLF.pdf (455.19 KB)
Aplicación de Algoritmos Evolutivos de Descubrimiento de Subgrupos en e-Learning: un Caso de Estudio, Romero, C., González P., Ventura S., del Jesus M. J., and Herrera F. , V Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), Tenerife (Spain), p.493-500, (2007)
Analysis of the Performance of a Semantic Interpretability-Based Tuning and Rule Selection of Fuzzy Rule-Based Systems by Means of a Multi-Objective Evolutionary Algorithm, Gacto, M. J., Alcalá R., and Herrera F. , LNAI 6097, June, Córdoba, p.228-238, (2010)
Analysis of the Impact of Using Different Diversity Functions for the Subgroup Discovery Algorithm NMEEF-SD, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , 5th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), April, Paris (France), p.17-23, (2011) PDF icon 2011 - GEFS.pdf (6.67 MB)
Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection, Fernández, A., del Jesus M. J., and Herrera F. , 4th International Workshop on Genetic and Evolutionary Fuzzy Systems (GEFS), March, Mieres (Spain), p.69-74, (2010)
Analysing Concentrating Photovoltaics Technology through the use of Emerging Pattern Mining, García-Vico, A.M., Montes J., Aguilera J., Carmona C. J., and del Jesus M. J. , Proceedings of the 11th International Conference on Soft Computing Models in Industrial and Environmental Applications, (2016) PDF icon 2016 - SOCO.pdf (803.02 KB)
Análisis visual de técnicas no supervisadas de deep learning con el paquete dlvisR, Charte, David, Charte Francisco, and Herrera F. , XVII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2016), 9, Salamanca (Spain), p.895–904, (2016) PDF icon 2016-CAEPIA-dlvisR.pdf (2.56 MB)
Análisis preliminar de marcos tecnológicos en data stream, Puentes, F., Pérez-Godoy M.D., González P., and del Jesus M. J. , II Workshop en Big Data y análisis de datos escalable, 10, Granada (España), p.1117-1122, (2018)
Análisis of Evolutionary Prototype Selection by means of a Data Complexity Measure based on Class Separabilty, Cano, J. R., García S., Herrera F., and Bernadó-Mansilla E. , Actas del Taller de Minería de Datos y Aprendizaje (TAMIDA), Zaragoza, p.145-152, (2007)
Análisis descriptivo mediante aprendizaje supervisado basado en patrones emergentes, Carmona, C. J., Pulgar-Rubio F., García-Vico A.M., González P., and del Jesus M. J. , VII Simposio de Teoría y Aplicaciones de Minería de Datos, p.685-694, (2015) PDF icon 2015 - TAMIDA-a.pdf (251.88 KB)
Análisis del virus de la gripe A mediante descubrimientos de subgrupos difusos, Carmona, C. J., Chrysostomou C., Seker H., and del Jesus M. J. , VII Simposio de Teoría y Aplicaciones de Minería de Datos (TAMIDA), September, Madrid (Spain), p.1313-1322, (2013) PDF icon 2013 - TAMIDA.pdf (294.44 KB)
Análisis del impacto de datos desbalanceados en el rendimiento predictivo de redes neuronales convolucionales, Pulgar-Rubio, F., Rivera-Rivas A.J., Charte Francisco, and Díaz María J. del Jesu , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.1213–1218, (2018) PDF icon 2018-CAEPIA-DesbalanceoCNNs.pdf (228.43 KB)
Análisis de Diferentes Tipos de Reglas en Sistemas Difusos Evolutivos para Minería de Patrones Emergentes, García-Vico, A.M., Carmona C. J., and del Jesus M. J. , Proc. of the XII Spanish Conference on Metaheuristics, Evolutive and Bioinspired Algorithms (MAEB 2017), p.876–885, (2017) PDF icon 2017-Garcia-MAEB2017.pdf (137.29 KB)
An Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Proceedings of the 8th Online World Conference on Soft Computing in Industrial Applications, September, (2003)
An Study on Data Mining Methods for Short-Term Forecasting of the Extra Virgin Olive Oil Price in the Spanish Market, Pérez, P., Frías M. P., Pérez-Godoy M.D., Rivera-Rivas A.J., Jesus M. J. d., Parras M., and Torres F. J. , 2008 Eighth International Conference on Hybrid Intelligent Systems, Sep., p.943-946, (2008)
An Improved Multi-Objective Genetic Algorithm for Tuning Linguistic Fuzzy System, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the 2008 International Conference on Information Processing and Management of Uncertainty in Knowledge-Based Systems (IPMU), June, p.1121-1128, (2008)
An evolutionary paradigm for designing fuzzy rule-based systems from examples, Cordón, O., del Jesus M. J., Herrera F., and Lozano Manuel , 10, p.139 - 144, (1997)
An evolutionary fuzzy system for the detection of exceptions in subgroup discovery, Carmona, C. J., González P., García-Domingo B., del Jesus M. J., and Aguilera J. , International Fuzzy Systems Applications World Congress (IFSA), July, Edmonton (Canada), p.74-79, (2013) PDF icon 2013 - IFSA.pdf (1.94 MB)
An ensemble strategy for forecasting the extra-virgin olive oil price in Spain, Rivera-Rivas, A.J., Pérez-Godoy M.D., Charte Francisco, Pulgar-Rubio F., and del Jesus M. J. , International work-conference on Time Series, ITISE 2015, 7, Granada (Spain), p.506–516, (2015) PDF icon 2015-ITISE-ForecastOliveOil.pdf (547.65 KB)
An ensemble method for time series forecasting with simple exponential smoothing, del Jesus, M. J., Martínez Francisco, Pérez-Godoy M.D., Rivera-Rivas A.J., and Frías María Pilar , Conference Computational and Mathematical Methods in Science and Engineering, 07, Rota, Cádiz (Spain), (2014)
An Approximation to Deep Learning Touristic-Related Time Series Forecasting, Trujillo, Daniel, Rivera-Rivas A.J., Charte Francisco, and del Jesus M. J. , 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, 11, Madrid (Spain), p.448–456, (2018) PDF icon 2018-IDEAL-LSTMTouristic.pdf (2.13 MB)
An Analysis of the Rule Weights and Fuzzy Reasoning Methods for Linguistic Rule Based Classification Systems Applied to Problems with Highly Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , International Workshop on Fuzzy Logic and Applications (WILF), July, Genova (Italy), p.170-179, (2007)
An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery, Carmona, C. J., González P., del Jesus M. J., and Herrera F. , IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), August, ICC Jeju, Jeju Island, Korea, p.1706-1711, (2009) PDF icon 2009 - FUZZIEEE.pdf (192.81 KB)
Alternative OVA Proposals for Cooperative Competitive RBFN Design in Classification Tasks, Charte, Francisco, Rivera-Rivas A.J., Pérez-Godoy M.D., and del Jesus M. J. , 12th International Work-Conference on Artificial Neural Networks (IWANN 2013), Tenerife (Spain), p.331-338, (2013) PDF icon 2013-IWANN-AlternativeOVA.pdf (146.42 KB)
Algoritmos simbióticos para la generación de redes RBF: comparativa entre codificaciones real y binaria, Parras-Gutiérrez, E., Rivas V. M., and del Jesus M. J. , VI Congreso Español sobre Metaheuristicas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, Málaga, p.341-348, (2009)
Algoritmo Genético Multi-Objetivo Avanzado para el ajuste de un sistema difuso aplicado al Control de Sistemas de Ventilación, Calefacción y Aire Acondicionado, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the Congreso Español sobre Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB), February, p.595-602, (2009)
Algoritmo GA-P Difuso para la Generación de Controladores en Edificios Inteligentes, Lopez, Antonio, Doctor Faiyaz, and Sánchez Luciano , Congreso español de metaheurísticas, algoritmos evolutivos y bioinspirados., 01, Córdoba (España), (2004)
Algoritmo Evolutivo de Extracción de reglas de Asociación aplicado a un problema de marketing, del Jesus, M. J., González P., Herrera F., and Mesonero M. , III Congreso Español de Metaheurísticas, Algoritmos Evolutivos y Bioinspirados(MAEB), Córdoba (Spain), p.102-104, (2004)
Ajuste genético lateral de las etiquetas lingüísticas en descubrimiento de subgrupos, Carmona, C. J., González P., Gacto M. J., and del Jesus M. J. , XVI Congreso Español sobre Tecnologías y Lógica Fuzzy (ESTYLF), February, Valladolid (Spain), p.271-276, (2012) PDF icon 2012 - ESTYLF.pdf (3.43 MB)
Ajuste Evolutivo Lateral y de Amplitud de etiquetas para Sistemas Basados en Reglas Difusas, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Simposio de Inteligencia Computacional (SICO), Granada (Spain), p.481-488, (2005)
Agglomerative Constrained Clustering Through Similarity and Distance Recalculation, González-Almagro, Germán, Suarez Juan Luis, Luengo Julián, Cano J. R., and García Salvador , International Conference on Hybrid Artificial Intelligence Systems, p.424-436, (2020)
Addressing Overlapping in Classification with Imbalanced Datasets: A First Multi-objective Approach for Feature and Instance Selection, Fernández, Alberto, del Jesus M. J., and Herrera F. , Intelligent Data Engineering and Automated Learning – IDEAL 2015, Cham, p.36–44, (2015)
Addressing Data-Complexity for Imbalanced Data-sets: A Preliminary Study on the Use of Preprocessing for C4.5, Luengo, J., Fernández A., Herrera F., and García S. , 9th International Conference on Intelligent Systems Designs and Applications (ISDA), p.523-528, (2009)
Adaptación de una asignatura avanzada de redes de computadores al modelo de docencia virtual dentro del marco del Espacio Europeo de Educación Superior, Rivera-Rivas, A.J., Carmona C. J., Pérez-Godoy M.D., and del Jesus M. J. , International Conference on Development and Innovation with New Technologies in Engineering Education, p.15-21, (2009) PDF icon 2009 - FINDIT.pdf (168.85 KB)
Adaptación curricular de la asignatura-Teoría de algortimos, Aguilera, José, and Balsas José R. , Jornadas sobre la enseñanza universitaria de la informática, 09, Alcalá de Henares (España), (2000)
Acceso restringido a calificaciones de alumnos a través de internet, Aguilera, José, Balsas José R., Martínez Francisco, and Rivas Victor M. , Simposio Español de informática distribuida, 09, Orense (España), (2000)
A Transformation Approach Towards Big Data Multilabel Decision Trees, Rivera-Rivas, A.J., Charte Francisco, Pulgar-Rubio F., and del Jesus M. J. , 14th International Work-Conference on Artificial Neural Networks (IWANN 2017), 6, Cádiz (Spain), p.73–84, (2017) PDF icon 2017-IWANN-BigDataMLDT.pdf (372.37 KB)
A Symbiotic CHC Co-evolutionary Algorithm for Automatic RBF Neural Networks Design, Parras-Gutiérrez, E., Rivas V. M., del Jesus M. J., and Merelo Juan J. , DCAI 2008: International Symposium on Distributed Computing and Artificial Intelligence, Salamanca, Volume 50/2009, p.663-671, (2008)
A Symbiotic CHC Co-evolutionary Algorithm for Automatic RBF Neural Networks Design, Parras-Gutiérrez, E., del Jesus M. J., Merelo Juan J., and Rivas Victor M. , International Symposium on Distributed Computing and Artificial Intelligence 2008 (DCAI 2008), Berlin, Heidelberg, p.663–671, (2009)
A Summary on the Study of the Medium-Term Forecasting of the Extra-Virgen Olive Oil Price, Rivera-Rivas, A.J., Pérez-Godoy M.D., del Jesus M. J., Pérez-Recuerda Pedro, Frías María Pilar, and Parras Manuel , Advances in Artificial Intelligence, Berlin, Heidelberg, p.263–272, (2011)
A study on the Use of the Fuzzy Reasoning Method based on the Winning Rule Vs. Voting Procedure for Classification with Imbalanced Data Sets, Fernández, A., García S., del Jesus M. J., and Herrera F. , Proceedings of the 9th International Work-Conference on Artificial Neural Networks (IWANN), June, San Sebastián (Spain), p.375-382, (2007)
A specialized lazy learner for time series forecasting, Martínez, Francisco, Frías M.P., Charte Francisco, and Rivera-Rivas A.J. , 17th International Conference on Computational and Mathematical Methods in Science and Engineering, CMMSE 2017, 7, Costa Ballena, Rota, Cáadiz (Spain), p.1397–1403, (2017) PDF icon 2017-CMMSE-SpecializedLazyLearner.pdf (211.11 KB)
A software tool to efficiently manage the energy consumption of HPC clusters, Cocaña-Fernández, A., Sánchez L., and Ranilla J. , 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), Aug, p.1-8, (2015)
A simple and fast hardware-accelerated point-in-polygon test, Martínez, Francisco, Ruiz Antonio J. Rueda, and Feito-Higueruela Francisco R. , GRAPP, (2007)
A Showcase of the Use of Autoencoders in Feature Learning Applications, Charte, David, Charte Francisco, del Jesus M. J., and Herrera F. , International Work-Conference on the Interplay Between Natural and Artificial Computation, 05/2019, p.412-421, (2019)
A proposal of Evolutionary Prototype Selection for Class Imbalance Problems, García, S., Cano J. R., Fernández A., and Herrera F. , Proceedings of the 7th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL), Volume 4224, p.1415-1423, (2006)
A Procedure for Extending Input Selection Algorithms to Low Quality Data in Modelling Problems with Application to the Automatic Grading of Uploaded Assignments, Otero, José Varela, Palacios Ana M., Suárez Rosario, Junco Luis, Couso Inés, and Sánchez Luciano , TheScientificWorldJournal, (2014)
A Preliminary Study on the Selection of Generalized Instances for Imbalanced Classification, García, S., Derrac J., Triguero I., Carmona C. J., and Herrera F. , Twenty Third International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA/AIE), Cordoba, p.601-610, (2010) PDF icon 2010 - IEA-AEI.pdf (211.57 KB)
A Preliminary Study on Selecting the Optimal Cut Points in Discretization by Evolutionary Algorithms, García, S., López V., Luengo J., Carmona C. J., and Herrera F. , 1st International Conference on Pattern Recognition Applications and Methods (ICPRAM), February, Villamoura - (Portugal), p.211-216, (2012) PDF icon 2012 - ICPRAM.pdf (106.28 KB)
A Preliminary Study on Mutation Operators in Cooperative Competitive Algorithms for RBFN Design, Pérez-Godoy, M.D., Rivera-Rivas A.J., Carmona C. J., and del Jesus M. J. , IEEE World Congress on Computational Intelligence (WCCI), p.349–355, (2010) PDF icon 2010 - IEEEWCCS - CoreA.pdf (606.64 KB)
A preliminary study on missing data imputation in evolutionary fuzzy systems of subgroup discovery, Carmona, C. J., Luengo J., González P., and del Jesus M. J. , IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), June, Brisbane (Australia), p.1-7, (2012) PDF icon 2012 - FUZZIEEE.pdf (1.63 MB)
A Preliminary Study on Crop Classification with Unsupervised Algorithms for Time Series on Images with Olive Trees and Cereal Crops , Rivera-Rivas, A.J., Pérez-Godoy M.D., Elizondo D., Deka Lipika, and del Jesus M. J. , 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), 08/2020, p.276-285, (2020)
A Preliminary Many Objective Approach for Extracting Fuzzy Emerging Patterns, Carmona, C. J., González P., García-Vico A.M., and del Jesus M. J. , 15th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2020), Volume 1268, p.100, (2020) PDF icon 2020 - SOCO.pdf (184.72 KB)
A Preliminar Analysis of CO2RBFN in Imbalanced Problems, Pérez-Godoy, M.D., Rivera-Rivas A.J., Fernández A., del Jesus M. J., and Herrera F. , Bio-Inspired Systems: Computational and Ambient Intelligence, Berlin, Heidelberg, p.57–64, (2009)
A pragmatic task design approach based on a Ward/Mellor real-time structured specification, Tuya, J., Sánchez L., Zurita R., and Corrales J. A. , Software Engineering –- ESEC '93, Berlin, Heidelberg, p.301–312, (1993)
A practical tutorial on autoencoders for nonlinear feature fusion: Taxonomy, models, software and guidelines, Charte, David, Charte Francisco, García S., del Jesus M. J., and Herrera F. , XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (CAEPIA 2018), 10, Granada (Spain), p.949–950, (2018) PDF icon 2018-CAEPIA-TutorialAEs.pdf (59.39 KB)
A Performance Study of Concentrating Photovoltaic Modules Using Neural Networks: An Application with CO2RBFN, Rivera-Rivas, A.J., García-Domingo B., del Jesus M. J., and Aguilera J. , Soft Computing Models in Industrial and Environmental Applications, Berlin, Heidelberg, p.439–448, (2013)
A Pareto Based Ensemble with Feature and Instance Selection for Learning from Multi-Class Imbalanced Datasets, Fernández, A., Carmona C. J., del Jesus M. J., and Herrera F. , Proc. of the XVIII Conferencia de la Asociación Española para la Inteligencia Artificial (XVIII CAEPIA), p.1316-1317, (2018) PDF icon 2018 - CAEPIA-262.pdf (63.54 KB)
A Novel Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for High Dimensional Problems, Berlanga, F. J., del Jesus M. J., and Herrera F. , 3rd International Workshop on Genetic and Evolving Fuzzy Systems (GEFS), WittenBommerholz (Germany), p.101-106, (2008)
A Nearest Hyperrectangle Monotonic Learning Method, García, Javier, Cano J. R., and García S. , Proceedings of the 11th International Conference Hybrid Artificial Intelligent Systems, 2016, Seville, Spain, April 18-20, 2016, p.311–322, (2016)
A Multiobjective Genetic Fuzzy System with Imprecise Probability Fitness for Vague Data, Sánchez, L., Couso I., and Casillas J. , 2006 International Symposium on Evolving Fuzzy Systems, Sep., p.131-136, (2006)
A multiobjective genetic algorithm for feature selection and granularity learning in fuzzy-rule based classification systems, Cordón, O., Herrera F., del Jesus M. J., and Villar P , 08, Volume 3, p.1253 - 1258 vol.3, (2001)
A Multiobjective Evolutionary Algorithm for Tuning Fuzzy Rule Based Systems with Measures for Preserving Interpretability, Gacto, M. J., Alcalá R., and Herrera F. , Proceedings of the Joint International Fuzzy Systems Association World Congress and the European Society for Fuzzy Logic and Technology Conference (IFSA), July, Lisbon, Portugal, p.1146-1151, (2009)
A Multi-Objective Evolutionary Algorithm for Rule Selection and Tuning on Fuzzy Rule-Based Systems, Alcalá, R., Alcalá-Fdez J., and Gacto M. J. , Proceedings of the 16th IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), July, London (United Kingdom), p.1367-1372, (2007)
A Minimum-Risk Genetic Fuzzy Classifier Based on Low Quality Data, Palacios, Ana M., Sánchez Luciano, and Couso Inés , Hybrid Artificial Intelligence Systems, Berlin, Heidelberg, p.654–661, (2009)
A Minimum Risk Wrapper Algorithm for Genetically Selecting Imprecisely Observed Features, Applied to the Early Diagnosis of Dyslexia, Sánchez, Luciano, Palacios Ana, and Couso Inés , Lecture Notes in Computer Science - LNCS, 09, Volume 5271, p.608-615, (2008)
A GRASP Algorithm for Clustering, Cano, J. R., Cordón O., Herrera F., and Sánchez Luciano , Proceedings of the 8th Ibero-American Conference on Artifical Intelligence, Seville, Spain, November 12-15, 2002,, p.214–223, (2002)
A Genetic-Programming-Based Approach for the Learning of Compact Fuzzy Rule-Based Classification Systems, Berlanga, F. J., del Jesus M. J., Gacto M. J., and Herrera F. , The Eighth International Conference on Artificial Intelligence and Soft Computing (ICAISC), Volume 4029, Zakopane (Poland), p.182-191, (2006)
A fuzzy definition of mutual information with application to the design of genetic fuzzy classifiers, Sánchez, Luciano, Suárez María, and Couso Inés , International Conference on Machine Intelligencea: ACIDCA-ICMI , 01, Tunez, (2005)
A first study on the use of fuzzy rule based classification systems for problems with imbalanced data sets, del Jesus, M. J., Fernández A., García S., and Herrera F. , Proceedings of the Symposium on Fuzzy Systems in Computer Science (FSCS), September, Magdeburg (Germany), p.63-72, (2006)
A first study on bagging fuzzy rule-based classification systems with multicriteria genetic selection of the component classifiers, Cordón, O., Quirin A., and Sánchez L. , 2008 3rd International Workshop on Genetic and Evolving Systems, March, p.11-16, (2008)
A First Attempt on Monotonic Training Set Selection, Cano, J. R., and García S. , Hybrid Artificial Intelligent Systems, Cham, p.277–288, (2018)
A First Approximation to the Effects of Classical Time Series Preprocessing Methods on LSTM Accuracy, Viedma, Daniel Trujillo, Rivera-Rivas A.J., Charte Francisco, and del Jesus M. J. , International Work-Conference on Artificial Neural Networks, 05/2019, p.270-280, (2019)
A first approach towards a fuzzy decision tree for multilabel classification, Prati, Ronaldo C., Charte Francisco, and Herrera F. , 2017 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE), 7, Naples (Italy), p.1–6, (2017) PDF icon 2017-IEEE-FuzzyDTMLC.pdf (299.08 KB)
A First Approach to Handle Emergining Patterns Mining on Big Data Problems: The EvAEFP-Spark Algorithm, García-Vico, A.M., González P., del Jesus M. J., and Carmona C. J. , Proc. of the 2017 IEEE International Conference on Fuzzy Systems, p.1-6, (2017) PDF icon 2017-Garcia-FuzzIEEE.pdf (383.81 KB)
A First Approach to Face Dimensionality Reduction Through Denoising Autoencoders, Pulgar-Rubio, F., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. , 19th International Conference on Intelligent Data Engineering and Automated Learning, IDEAL 2018, 11, Madrid (Spain), p.439–447, (2018) PDF icon 2018-IDEAL-DimensionalityDAE.pdf (2.45 MB)
A First Approach to Deal with Imbalance in Multi-label Datasets, Charte, Francisco, Rivera-Rivas A.J., del Jesus M. J., and Herrera F. , 8th International Conference on Hybrid Artificial Intelligent Systems (HAIS 2013), 9, Salamanca (Spain), p.150-160, (2013) PDF icon 2013-HAIS-ImbalanceMultilabel.pdf (194.4 KB)
A first analysis of the effect of local and global optimization weights methods in the cooperative-competitive design of RBFN for imbalanced environments, Pérez-Godoy, M.D., Rivera-Rivas A.J., del Jesus M. J., and Martínez Francisco , The 2013 International Joint Conference on Neural Networks (IJCNN), Aug, p.1-8, (2013)
A fast genetic method for inducting linguistically understandable fuzzy models, Sánchez, L. , Proceedings Joint 9th IFSA World Congress and 20th NAFIPS International Conference (Cat. No. 01TH8569), July, Volume 3, p.1559-1563 vol.3, (2001)
A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based Systems, Gacto, M. J., Alcalá R., and Herrera F. , Fuzzy Logic and Applications, Berlin, Heidelberg, p.99–106, (2011)
A double axis classi, Gacto, M. J., Alcalá R., and Herrera F. , 9th International Workshop on Fuzzy Logic and Applications (WILF), (2011)
A coevolutionary genetic algorithm able to learn a FRBS and detect the less informative instances in low quality problems, Sánchez, Luciano , Congreso Español sobre tecnologías y lógica fuzzy, 01, Huelva (España), (2010)
A case of study with the Clustering R library to measure the quality of cluster algorithms, Pérez-Martos, L.A., García-Vico A.M., González P., and Carmona C. J. , International Conference on Hybrid Artificial Intelligence Systems (HAIS) - Salamanca 5-8 septembre, p.88-97, (2022)
A Baseline Learning Genetic Fuzzy Classifier Based on Low Quality Data., Palacios, Ana, Sánchez Luciano, and Couso Inés , 01, p.803-808, (2009)
Book Chapter
Visualización de medios participativos en entornos urbanos, Jiménez-Perez, Juan Roberto, Martínez Francisco, and Aguilera-García Ángel , Gestión de información urbana tridimiensional, p.151-157, (2011)
Un estudio empírico preliminar sobre los tests estadísticos más habituales en el aprendizaje automático, Herrera, F., Hervas-Martínez Cesar, Otero J, and Sánchez Luciano , Tendencias de la minería de datos en España, Number 403-412, Santander (España), (2004)
Tuning fuzzy partitions or assigning weights to fuzzy rules: which is better?, Sánchez, Luciano, and Otero José , Accuracy Improvements in Linguistic Fuzzy Modeling, Berlin, Heidelberg, p.366–385, (2003)
Técnicas de reducción de datos en KDD, Cano, J. R., and Herrera F. , Minería de datos: Técnicas y Aplicaciones, Number 13-33, Sevilla (España), (2005)
Subgroup Discovery with Linguistic Rules, del Jesus, M. J., González P., and Herrera F. , Fuzzy Sets and Their Extensions: Representation, Aggregation and Models, Berlin, Heidelberg, p.411–430, (2008)
Strategies for Scaling Up Evolutionary Instance Reduction Algorithms for Data Mining, Cano, J. R., Herrera F., and Lozano Manuel , Evolutionary Computation in Data Mining, Berlin, Heidelberg, p.21–39, (2005)
Selección Evolutiva Estratificada de Conjuntos de Entrenamiento para la Obtención de Bases de Reglas con un Alto Equilibrio entre Precisión e Interpretabilidad, Cano, J. R., Herrera F., and Lozano M. , Tendencias de la Minería de Datos en Spain., p.263 - 274, (2004)
Replacement Strategies to Maintain Useful Diversity in Steady-State Genetic Algorithms, Lozano, Manuel, Herrera F., and Cano J. R. , 01, p.85-96, (2005)
Proyecto KEEL: Desarrollo de una herramienta para el análisis e implementación de algoritmos de extracción de conocimiento evolutivos, Alcala-Fdez, Jesus, del Jesus M. J., Garrell Josep-Maria, Herrera F., Martínez Cesar, and Sánchez Luciano , 01, p.413-424, (2004)
PRESETEMP: Predicción de Series Temporales mediante técnicas de Minería de Datos, Rivas, V. M., Parras-Gutiérrez E., Pérez-Godoy M.D., Rivera-Rivas A.J., Olmo M. J., Arenas M.G., Fernandez-Montoya A., and Cillero M. , Proyectos de Investigación 2009-10, (2012)
Operaciones Booleanas sobre polígonos, Martínez, Francisco, Aguilera-García Ángel, and Jiménez-Perez Juan Roberto , Gestión de información urbana tridimiensional, Jaén (España), p.101-110, (2011)
On the Usefulness of MOEAs for Getting Compact FRBSs Under Parameter Tuning and Rule Selection, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Multi-Objective Evolutionary Algorithms for Knowledge Discovery from Databases, Berlin, Heidelberg, p.91–107, (2008)
On the use of Multiobjective Genetic Algorithms to Improve the Accuracy-Interpretability Trade-Off of Fuzzy Rule-Based Systems, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Multi-objective Evolutionary Algorithms for Knowledge Discovery from Data Bases, Volume 98, (2008)
LA DESCOMPOSICIÓN MULTI-L-REP DE POLIEDROS, Joan-Arinyo, Robert, Torres-Cantero Juan Carlos, and Feito Francisco Ramón , Hacad: Herramientas avanzadas en CAD, Jaén (España), p.207-222, (2007)
Introduction to the Experimental Design in the Data Mining Tool KEEL, Alcala-Fdez, Jesus, Garcia S, Sánchez Luciano, Robles I, del Jesus M. J., Bernado-Mansilla E, Peregrin Antonio, and Herrera F. , 01, p.1-25, (2010)
Introducción de información geográfica en terrenos 3D, Aguilera-García, Ángel, Jiménez-Perez Juan Roberto, and Martínez Francisco , Gestión de información urbana tridimensional, p.71-82, (2011)
Instance Selection Using Evolutionary Algorithms: An Experimental Study, Cano, J. R., Herrera F., and Lozano Manuel , Advanced Techniques in Knowledge Discovery and Data Mining, London, p.127–152, (2005)
GA-P Based Search of Structures and Parameters of Dynamital Process Models, Benítez, José Manuel, Cordón O., Hoffmann Frank, and Rajkumar Roy , Advances in Soft Computing, p.371-380, (2003)
GA-P based Feature Selection and Classification combining different Methods of Texture Analysis, Cano, Fernando, Junco Luis, and Sánchez Luciano , 09, p.209-219, (2000)
Fuzzy Rule Reduction and Tuning of Fuzzy Logic Controllers for a HVAC System, Alcalá, R., Alcalá-Fdez J., Gacto M. J., and Herrera F. , Fuzzy Applications in Industrial Engineering, Studies in Fuzziness and Soft Computing, Volume 201, p.89-117, (2006)
Extacción de conocimiento con algoritmos evolutivos y reglas difusas, Díaz, María José del, González P., and Herrera F. , Introducción a la minería de datos, p.383-420, (2004)
Evolutionary Induction of Descriptive Rules in a Market Problem, del Jesus, M. J., González P., Herrera F., and Mesonero M. , Intelligent Data Mining. Techniques and Applications, Studies in Computational Intelligence, Volume 5, p.267-292, (2005)
Diplomatura de estadística e ingeniería técnica de informática de gestión, Sánchez-Gómez, María del Carmen, Aguilera José, and Cano-Ortega Antonio , Planes de acción tutorial en la universidad, Jaén, p.249-270, (2009)
Different Proposals to Improve the Accuracy of Fuzzy Linguistic Modeling, Cordón, O., Herrera F., del Jesus M. J., Villar Pedro, and Zwir Igor , Fuzzy If-Then Rules in Computational Intelligence: Theory and Applications, Boston, MA, p.189–221, (2000)
De la teoría a la práctica: una reflexión sobre el EEES en aula, Romero, Samuel, Cano J. R., Prados-Suarez María Belen, and Rivero-Cejudo Maria Linarejos , Adaptación del profesorado universitario al espacio europeo de educación superior mediante el uso de nuevas tecnologías, Number 69-77, Jaén (España), (2005)
CO2RBFN for Short and Medium Term Forecasting of the Extra Virgin Olive Oil Price, Pérez-Godoy, M.D., Pérez P., Frías M.P., Rivera-Rivas A.J., Carmona C. J., and Parras M. , Studies in Computational Intelligence, Volume 284, p.113-125, (2010) PDF icon 2010 - NICSO.pdf (589.38 KB)
Applying Subgroup Discovery Based on Evolutionary Fuzzy Systems for Web Usage Mining in E-Commerce: A Case Study on OrOliveSur.com, Carmona, C. J., and del Jesus M. J. , Foundations and Applications of Intelligent Systems, p.591-602, (2013) PDF icon 2012 - ISKE.pdf (354.7 KB)
A Study on the Combination of Evolutionary Algorithms and Stratified Strategies for Training Set Selection in Data Mining, Cano, J. R., Herrera F., and Lozano M. , Soft Computing: Methodologies and Applications, p.271-284, (2005)
A Review on Evolutionary Prototype Selection, García, S., Cano J. R., and Herrera F. , Intelligent Systems for Automated Learning and Adaptation: Emerging Trends and Applications, p.92–113, (2010)
A Multiobjective Genetic Learning Process for joint Feature Selection and Granularity and Contexts Learning in Fuzzy Rule-Based Classification Systems, Cordón, O., del Jesus M. J., Herrera F., Magdalena Luis, and Villar Pedro , Interpretability Issues in Fuzzy Modeling, Berlin, Heidelberg, p.79–99, (2003)
- A Multiobjective Genetic Algorithm for Feature Selection and Data Base Learning in Fuzzy-Rule Based Classification Systems, Cordón, O., Herrera F., del Jesus M. J., Magdalena L., Sánchez A.M., and Villar P. , Intelligent Systems for Information Processing, Amsterdam, p.315 - 326, (2003)
A first approach in the class noise filtering approaches for Fuzzy Subgroup Discovery, Carmona, C. J., and Luengo J. , Advances in Intelligent Systems and Computing, Volume 368, p.387-399, (2015) PDF icon 2015 - SOCO.pdf (530.94 KB)