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2021

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)

1-s2.0-S0020025521002024-main.pdf (1.79 MB)

2020

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)

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)

1-s2.0-S1566253519300880-main.pdf (895.14 KB)

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)

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)

FCharte-EvoAAAOpen.pdf (820.83 KB)

2019

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)

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)

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)

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)

2019-NeucomDealingDifficultLabels.pdf (4.77 MB)

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)

Charte2019_Article_PredtoolsTSRPackageForStreamli.pdf (390.07 KB)

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)

2019-NeucomRemedial-HwR.pdf (2.83 MB)

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)

RJ-2019-004.pdf (204.01 KB)

2018

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)

2018-IDEAL-DimensionalityDAE.pdf (2.45 MB)

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)

125905686.pdf (3.86 MB)

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)

2018-IDEAL-LSTMTouristic.pdf (2.13 MB)

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)

2018-CAEPIA-DesbalanceoCNNs.pdf (228.43 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)

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)

2018-EAIC18-HardwareAltoRend-compressed.pdf (431.68 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)

2018-Neucom-TipsMLCCometa-compressed.pdf (1017.86 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)

2018-CAEPIA-TurismoLSTMs.pdf (127.66 KB)

2017

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 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)

2017-CMMSE-SpecializedLazyLearner.pdf (211.11 KB)

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)

2017-IWANN-BigDataMLDT.pdf (372.37 KB)

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)

2017-CACE-Biomasa.pdf (1.28 MB)

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)

2017-EAIC17-EvolucionGPUs.pdf (2.1 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)

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)

2017IWANN-Biomass.pdf (158.82 KB)

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)

Pulgar2017_Chapter_OnTheImpactOfImbalancedDataInC.pdf (634.69 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)

2017-EAIC17-FPGAsEnsenanza.pdf (1.48 MB)

2016

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)

2016 - HAIS - CoreC.pdf (203.25 KB)

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)

2016-EAIC16-Paralelismo.pdf (1.16 MB)

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)

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)

2016-CAEPIA-MLSMOTE.pdf (579.04 KB)

Multilabel Classification: Problem Analysis, Metrics and Techniques, Herrera, F., Charte Francisco, Rivera-Rivas A.J., and del Jesus M. J. , (2016)

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)

Complexity.pdf (1.56 MB)

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)

RUMDR.pdf (294.87 KB)

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)

2015

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)

2015-GarciaDomingo-ESWA.pdf (1.22 MB)

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)

2015-Neucom-AddressingImbalance.pdf (546.81 KB)

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)

2015-ITISE-ForecastOliveOil.pdf (547.65 KB)

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)

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)

2015-KBS-MLSMOTE.pdf (1.56 MB)

{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)

2015-EUROCON-QUINTA.pdf (2.03 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)

2015-HAIS-REMEDIAL.pdf (1.04 MB)

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)

2015 - BD.pdf (374.17 KB)

2014

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)

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)

2014-HAIS-ConcurrenceLabels.pdf (1.12 MB)

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)

2014-TNNLS-LI-MLC.pdf (1.85 MB)

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)

2014-IDEAL-MLeNN.pdf (184.04 KB)

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)

2014-EAIC14-AsignaturaDisenoServ.pdf (864.57 KB)

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)

2014-Perez-ASOC.pdf (926.82 KB)

2013

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 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)

2013-HAIS-ImbalanceMultilabel.pdf (194.4 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)

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)

2013-IWANN-AlternativeOVA.pdf (146.42 KB)

2012

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)

2012-HAIS-LabelReduction.pdf (171.47 KB)

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)

2011

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 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)

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)

2011-IWANN-MultilabelTestingCO2RBFN.pdf (131.76 KB)

2010

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)

2010 - IEEEWCCS - CoreA.pdf (606.64 KB)

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)

2010 - NICSO.pdf (589.38 KB)

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)

2010-Perez-Godoy-IJHIS.pdf (434.9 KB)

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)

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)

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)

2010 - ESTYLF.pdf (587.96 KB)

2009

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)

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)

2009 - FINDIT.pdf (168.85 KB)

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)

2009 - IWANN - CoreB.pdf (190.56 KB)

2008

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)

2007

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)

2005

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)

2004

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)

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)

2003

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)

2002

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)

2000

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)

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)

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)

1998

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)

1997

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)