Publicaciones
2024
Pérez Godoy, M. D. . ., Molina, M. ., del Rio, F. M. ., Elizondo, D. A., Charte Ojeda, F. ., & Rivera, A. J. (2024). DESReg: Dynamic Ensemble Selection library for Regression tasks. Neurocomputing. Recuperado de https://api.semanticscholar.org/CorpusID:268283297
PID2019-107793GB-I00
Ayasi, B. ., García-Vico, Ángel M. ., Carmona del Jesus, C. J. ., & M, S. . (2024). Advancing computational frontiers: Spiking neural networks in high-energy efficiency computing across diverse domains.
PID2019-107793GB-I00
Germán Morales, M. ., Rivera Rivas, A. J. ., Charte Ojeda, F. ., De La Casa-Higueras, J. ., Tejero, J. A., & del Jesus, M. J. . (2024). Modelado de módulos fotovoltaicos bifaciales mediante técnicas de aprendizaje automático.
PID2019-107793GB-I00
de la Rosa de la Rosa, D. ., Charte Ojeda, F. ., & del Jesus, M. J. . (2024). Detección automática no supervisada de imágenes de fototrampeo vacías.
PID2019-107793GB-I00
Vázquez, I. ., Ayasi, B. ., Seker, H. ., Luengo, J. ., Sedano, J. ., & García-Vico, Á.M. . (2024). Combining traditional and spiking neural networks for energy-efficient detection of Eimeria parasites. Applied Soft Computing, 160, 111681. https://doi.org/https://doi.org/10.1016/j.asoc.2024.111681
PID2019-107793GB-I00
2023
Cabrera-Bermejo, M. I., Del Jesus, M. J., Rivera, A. J., Elizondo, D. ., Charte Ojeda, F. ., & Pérez-Godoy, M. D. (2023). Analysis of Transformer Model Applications. 231–243. Berlin, Heidelberg: Springer-Verlag. https://doi.org/10.1007/978-3-031-40725-3_20
PID2019-107793GB-I00
Padilla, D. ., Padilla Rascón, M. A. . ., Cámara, R. ., & Carmona del Jesus, C. J. . (2023). A First Evolutionary Fuzzy Approach for Change Mining with Smart Bands. 14113 LNAI, 171-181. Springer Science and Business Media Deutschland GmbH. https://doi.org/10.1007/978-3-031-42935-4_14
PID2019-107793GB-I00
Pérez Martos, L. A. . ., García-Vico, Ángel M., González, P. ., & Carmona del Jesus, C. J. . (2023). An Evolutionary Fuzzy System for Multiclustering in Data Streaming. 230, 33-43. Elsevier B.V. https://doi.org/10.1016/J.PROCS.2023.12.058
PID2019-107793GB-I00
de la Rosa de la Rosa, D. ., Álvarez, A. ., Pérez, R. ., Garrote, G. ., Rivas, A. R., Del Jesus, M. J., & Charte Ojeda, F. . (2023). NOSpcimen: A First Approach to Unsupervised Discarding of Empty Photo Trap Images. https://doi.org/10.1007/978-3-031-43078-7_4 (Original work published)
PID2019-107793GB-I00
Biedma-Rdguez, C. ., Gacto, M. J., Anguita-Ruiz, A. ., Alcalá, R. ., Aguilera, C. M., & Alcala-Fdez, J. . (2023). Learning positive-negative rule-based fuzzy associative classifiers with a good trade-off between complexity and accuracy. Fuzzy Sets and Systems, 465, 108511. https://doi.org/https://doi.org/10.1016/j.fss.2023.03.014
PID2019-107793GB-I00
Arteaga, M. ., Gacto, M. J., Galende, M. ., Alcala-Fdez, J. ., & Alcalá, R. . (2023). Enhancing soft computing techniques to actively address imbalanced regression problems. Expert Systems With Applications, 234, 121011. https://doi.org/https://doi.org/10.1016/j.eswa.2023.121011
PID2019-107793GB-I00
Rivera, A. ., Muñoz, C. ., Pérez-Goody, M. ., de San Pedro, S. ., Charte Ojeda, F. ., Elizondo, D. ., … del Jesus, M. . (2023). XAIRE: An ensemble-based methodology for determining the relative importance of variables in regression tasks. Application to a hospital emergency department. Artificial Intelligence in Medicine, 137, 102494. https://doi.org/https://doi.org/10.1016/j.artmed.2023.102494
PID2019-107793GB-I00
Rivera, A. J., Dávila, M. A., Elizondo, D. ., del Jesus, M. J., & Charte Ojeda, F. . (2023). mldr.resampling: Efficient reference implementations of multilabel resampling algorithms. Neurocomputing, 559, 126806. https://doi.org/https://doi.org/10.1016/j.neucom.2023.126806
PID2019-107793GB-I00
Carmona del Jesus, C. J. ., Germán Morales, M. ., Elizondo, D. ., Ruiz-Rodado, V. ., & Grootveld, M. . (2023). Urinary Metabolic Distinction of Niemann-Pick Class 1 Disease through the Use of Subgroup Discovery. Metabolites, 13. https://doi.org/10.3390/metabo13101079
PID2019-107793GB-I00
Cabrera-Bermejo, M. I., Del Jesus, M. J., Rivera, A. J., Elizondo, D. ., Charte, F. ., & Pérez-Godoy, M. D. (2023). Analysis of Transformer Model Applications (P. G. Bringas, H. P. García, F. J. M. de Pisón, F. M. Álvarez, A. T. Lora, álvaro . Herrero, … E. . Corchado, Eds.). Cham: Springer Nature Switzerland.
PID2019-107793GB-I00
Martos, L. A. P., García-Vico, Ángel M., González, P. ., & del Jesus, C. J. C. (2023). A Multiclustering Evolutionary Hyperrectangle-Based Algorithm. International Journal of Computational Intelligence Systems, 16. https://doi.org/10.1007/S44196-023-00341-3
PID2019-107793GB-I00
García-Vico, Ángel M. ., Carmona del Jesus, C. J. ., González García, P. ., & del Jesus, M. J. . (2023). A distributed evolutionary fuzzy system-based method for the fusion of descriptive emerging patterns in data streams. Information Fusion. https://doi.org/10.1016/j.inffus.2022.10.028
PID2019-107793GB-I00
Pérez-Martos, L. ., García-Vico, Ángel M. ., González García, P. ., & Carmona del Jesus, C. J. . (2023). Clustering: An R library to facilitate the analysis and comparison of cluster algorithms. Progress in Artificial Intelligence.
PID2019-107793GB-I00
2022
Rodríguez, C. B., Gacto, M. J., Ruiz, A. A., Fernández, J. A., & Fernández, R. A. (2022). Transparent but Accurate Evolutionary Regression Combining New Linguistic Fuzzy Grammar and a Novel Interpretable Linear Extension. Springer. https://doi.org/10.1007/s40815-022-01324-w (Original work published)
PID2019-107793GB-I00
Rivas, A. R., Pérez-Godoy, M. ., Elizondo, D. ., Deka, L. ., & Del Jesus, M. J. (2022). Analysis of clustering methods for crop type mapping using satellite imagery. Neurocomputing, 492. https://doi.org/10.1016/j.neucom.2022.04.002 (Original work published)
PID2019-107793GB-I00
Pérez-Martos, L. ., García-Vico, Ángel M. ., González García, P. ., & Carmona del Jesus, C. J. . (2022). A case of study with the Clustering R library to measure the quality of cluster algorithms. 88-97.
PID2019-107793GB-I00
Sáez-Castillo, A. J., Conde-Sánchez, A. ., & Martínez, F. . (2022). DGLMExtPois: Advances in Dealing with Over and Under-dispersion in a Double GLM Framework. The R Journal, 14, 121-140. https://doi.org/10.32614/RJ-2023-002
PID2019-107793GB-I00
Carmona del Jesus, C. J. ., González García, P. ., & García-Vico, Ángel M. . (2022). Gamificación mediante juegos de bloques en asignaturas del ámbito de la Inteligencia Artificial en el Grado en Ingeniería Informática. Presentado en. Madrid.
Martínez, F. ., Charte Ojeda, F. ., Frías Bustamante, M. del P. ., & Martínez-Rodríguez, A. M. (2022). Strategies for time series forecasting with generalized regression neural networks. Neurocomputing, 491, 509-521. https://doi.org/10.1016/j.neucom.2021.12.028
PID2019-107793GB-I00
del Rio, F. M. ., Frías, M. ., Pérez Godoy, M. D. . ., & Rivera Rivas, A. J. . (2022). Time Series Forecasting by Generalized Regression Neural Networks Trained With Multiple Series. IEEE Access, 10, 3275-3283. https://doi.org/10.1109/ACCESS.2022.3140377
PID2019-107793GB-I00
Carmona del Jesus, C. J. ., González García, P. ., & García-Vico, Ángel M. . (2022). Uso de metodologías de aprendizaje invertido para resolución de la parte práctica en asignaturas del grado de ingeniería informática. Presentado en. Santiago de Compostela.
2021
Escobar, A. ., González García, P. ., & del Jesus, M. J. . (2021). Revisión y análisis de conceptos en Inteligencia Artificial Explicable. Una aproximación a la unificación de la terminología.
PID2019-107793GB-I00
Puentes-Marchal, F. ., Pérez-Godoy, M. ., González, P. ., & del Jesus, M. J. . (2021). Implementation of Data Stream Classification Neural Network Models Over Big Data Platforms. https://doi.org/10.1007/978-3-030-85099-9_22 (Original work published)
PID2019-107793GB-I00
García-Vico, Ángel M. ., Carmona del Jesus, C. J. ., González García, P. ., & del Jesus, M. J. . (2021). A cellular-based evolutionary approach for the extraction of emerging patterns in massive data streams. Expert Systems With Applications, 183, 115419.
DOC 00235; PID2019-107793GB-I00
Rojas, M. M., Gacto, M. J., Vitiello, A. ., Acampora, G. ., & Hidalgo, J. M. S. (2021). 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. Sensors, 21, 6461. https://doi.org/10.3390/s21196461
PID2019-107793GB-I00
Rubio, F. J. . P., Charte Ojeda, F. ., Rivera Rivas, A. J. ., & del Jesus, M. J. . (2021). ClEnDAE: A classifier based on ensembles with built-in dimensionality reduction through denoising autoencoders. Information Sciences, 565, 146-176. https://doi.org/10.1016/j.ins.2021.02.060
TIN2015-68454-R; PID2019-107793GB-I00 / AEI /10.13039/501100011033
Pérez-Martos, L. ., González García, P. ., & Carmona del Jesus, C. J. . (2021). Clustering: Un paquete R para facilitar el análisis de algoritmos de agrupamiento. VI Congreso Español De Informática (CEDI). Presentado en.
PID2019-107793GB-I00
Gonzalez, M. ., González-Almagro, G. ., Triguero, I. ., Cano De Amo, J. R. . ., & García López, S. . (2021). Decomposition-Fusion for Label Distribution Learning. Information Fusion, 66, 64-75. https://doi.org/10.1016/j.inffus.2020.08.024 (Original work published 2021)
TIN2017-89517-P
García-Vico, Ángel M. ., Elizondo, D. ., Charte Ojeda, F. ., González García, P. ., & Carmona del Jesus, C. J. . (2021). E2PAMEA: un algoritmo evolutivo para la extraccióni eficiente de patrones emergentes difusos en entornos big data. Conferencia De La Asociación Española Para La Inteligencia Artificial (CAEPIA). Presentado en.
PID2019-107793GB-I00
González-Almagro, G. ., Luengo, J. ., Cano De Amo, J. R. . ., & García López, S. . (2021). Enhancing instance-level constrained clustering through differential evolution. Applied Soft Computing, 108, 1-19. https://doi.org/10.1016/j.asoc.2021.107435
TIN2017-89517-P; PP2019.PRI.I.06.
García-Vico, Ángel M. ., Seker, H. ., Carmona del Jesus, C. J. ., González García, P. ., & del Jesus, M. J. . (2021). FEPDS: Una propuesta para la extracción de patrones emergentes difusos en flujos continuos de datos. Presentado en.
DOC_0235, PID2019-107793GB-I00
Puentes, F. ., Pérez Godoy, M. D. . ., González García, P. ., & del Jesus, M. J. . (2021). Implementation of Data Stream Classification Neural Network Models Over Big Data Platforms. 272-280. Springer International Publishing. https://doi.org/10.1007/978-3-030-85099-9_22
TIN2015-68454-R, PID2019-107793GB-I00
Charte, D. ", Charte Ojeda, F. ., & Herrera, F. . (2021). Reducing Data Complexity using Autoencoders with Class-informed Loss Functions. IEEE Transactions on Pattern Analysis and Machine Intelligence, In Press. https://doi.org/10.1109/TPAMI.2021.3127698
PID2019-107793GB-I00
Charte, D. ", Sevillano-García, I. ., Lucena-González, M. J., Martín-Rodríguez, J. L., Charte Ojeda, F. ., & Herrera, F. . (2021). Slicer: Feature Learning for Class Separability with Least-Squares Support Vector Machine Loss and COVID-19 Chest X-Ray Case Study. En H. S. González, I. P. López, P. G. Bringas, H. . Quintián, & E. . Corchado (Eds.), Hybrid Artificial Intelligent Systems (HAIS 2021) (pp. 305-315). Cham: Springer International Publishing.
PID2019-107793GB-I00
Gonzalez, M. ., Luengo, J. ., Cano De Amo, J. R. . ., & García López, S. . (2021). Synthetic Sample Generation for Label Distribution Learning. Information Sciences, 544, 197-213. https://doi.org/10.1016/j.ins.2020.07.071 (Original work published 2021)
TIN2017-89517-P
2020
Charte Ojeda, F. . (2020). A Comprehensive and Didactic Review on Multilabel Learning Software Tools. IEEE Access, 8, 50330-50354. https://doi.org/10.1109/ACCESS.2020.2979787 (Original work published 2020)
TIN2015-68854-R
González-Almagro, G. ., Suarez, J. L., Luengo, J. ., Cano De Amo, J. R. . ., & García López, S. . (2020). Agglomerative Constrained Clustering Through Similarity and Distance Recalculation. 424-436. https://doi.org/10.1007/978-3-030-61705-9_35
Puentes, F. ., Pérez Godoy, M. D. . ., González García, P. ., & del Jesus, M. J. . (2020). An analysis of technological frameworks for data streams. Progress in Artificial Intelligence, 9, 239-261. https://doi.org/10.1007/s13748-020-00210-6 (Original work published 2020)
PID2019-107793GB-I00
González-Almagro, G. ., Luengo, J. ., Cano De Amo, J. R. . ., & García López, S. . (2020). DILS: Constrained clustering through dual iterative local search. Computers \& Operations Research, 121, 104979. https://doi.org/10.1016/j.cor.2020.104979
TIN2017- 89517-P; PP2016.PRI.I.02.
García-Vico, Ángel M. ., Charte Ojeda, F. ., González García, P. ., Elizondo, D. ., & Carmona del Jesus, C. J. . (2020). E2PAMEA: A fast evolutionary algorithm for extracting fuzzy emerging patterns in big data environments. Neurocomputing, 415, 60-73. https://doi.org/10.1016/j.neucom.2020.07.007 (Original work published 2020)
TIN2015-68454-R; BES-2016-07773; PID2019-107793GB-I00
Charte Ojeda, F. ., Rivera Rivas, A. J. ., Medina, J. ., & Espinilla, M. . (2020). El ecosistema de aprendizaje del estudiante universitario en la post-pandemia. Metodologías y herramientas. Enseñanza Y Aprendizaje De Ingeniería De Computadores. https://doi.org/10.30827/Digibug.64779
Charte Ojeda, F. ., Rivera Rivas, A. J. ., Martínez, F. ., & del Jesus, M. J. . (2020). EvoAAA: An evolutionary methodology for automated neural autoencoder architecture search. Integrated Computer-Aided Engineering, 27, 211-231. https://doi.org/10.3233/ICA-200619 (Original work published 2020)
García-Vico, Ángel M. ., Carmona del Jesus, C. J. ., González García, P. ., Seker, H. ., & del Jesus, M. J. . (2020). FEPDS: A Proposal for the Extraction of Fuzzy Emerging Patterns in Data Streams. IEEE Transactions on Fuzzy Systems, 28, 3193-3203. https://doi.org/10.1109/TFUZZ.2020.2992849 (Original work published 2020)
BES-2016-077738
González-Almagro, G. ., Rosales-Pérez, A. ., Luengo, J. ., Cano De Amo, J. R. . ., & García López, S. . (2020). Improving constrained clustering via decomposition-based multiobjective optimization with memetic elitism. GECCO ’20: Proceedings of the 2020 Genetic and Evolutionary Computation Conference, 333-341. https://doi.org/10.1145/3377930.3390187 (Original work published 2020)
TIN2017-89517-P; PP2016.PRI.I.02.
Gonzalez, M. ., Cano De Amo, J. R. . ., & García López, S. . (2020). ProLSFEO-LDL: Prototype Selection and Label- Specific Feature Evolutionary Optimization for Label Distribution Learning. Applied Sciences, 10, 3089. https://doi.org/10.3390/app10093089
TIN2017-89517-P