Fernández Hilario, A. L., Berlanga, F., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Genetic Cooperative-Competitive Fuzzy Rule Based Learning Method using Genetic Programming for Highly Imbalanced Data-Sets. 42-47. Lisbon (Portugal).
Maria José del Jesus Díaz
First name
Maria José
Last name
del Jesus Díaz
2009
Parras Gutiérrez, E., del Jesus Díaz, M. J., Merelo, J. J., & Rivas, V. M. (2009). A Symbiotic CHC Co-evolutionary Algorithm for Automatic RBF Neural Networks Design (J. M. Corchado, S. Rodríguez, J. Llinas, & J. M. Molina, Eds.). Berlin, Heidelberg: Springer Berlin Heidelberg.
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Hierarchical fuzzy rule based classfication systems with genetic rule selection for imbalanced data-sets. International Journal of Approximate Reasoning, 50, 561-577. https://doi.org/10.1016/j.ijar.2008.11.004
Rivera Rivas, A. J., Carmona, C. J., Pérez Godoy, M. D., & del Jesus Díaz, M. J. (2009). Adaptación de una asignatura avanzada de redes de computadores al modelo de docencia virtual dentro del marco del Espacio Europeo de Educación Superior. 15-21.
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Improving the Performance of Fuzzy Rule Based Classification Systems for Highly Imbalanced Data-sets Using an Evolutionary Adaptive Inference System. 5517, 294-301. Salamanca (Spain). (Original work published 2026)
Parras Gutiérrez, E., Rivas, V. M., & del Jesus Díaz, M. J. (2009). Algoritmos simbióticos para la generación de redes RBF: comparativa entre codificaciones real y binaria. 341-348. Málaga. (Original work published 2026)
Alcala-Fdez, J., Sánchez, L., García López, S., del Jesus Díaz, M. J., Ventura, S., Garrell, J., … Herrera Triguero, F. (2009). KEEL: A Software Tool to Assess Evolutionary Algorithms for Data Mining Problems. Soft Computing, 13, 307-318. https://doi.org/10.1007/s00500-008-0323-y
Carmona, C. J., González García, P., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). An analysis of evolutionary algorithms with different types of fuzzy rules in subgroup discovery. 1706-1711. ICC Jeju, Jeju Island, Korea. (Original work published 2026)
Carmona, C. J., González García, P., del Jesus Díaz, M. J., & Herrera Triguero, F. (2009). Non-dominated Multi-objective Evolutionary Algorithm Based on Fuzzy Rules Extraction for Subgroup Discovery. 5572, 573-580. Salamanca (Spain): Springer. (Original work published 2026)
Pérez Godoy, M. D., Rivas, A. R., Berlanga, F., & del Jesus Díaz, M. J. (2009). CO2RBFN: An evolutionary cooperative-competitive RBFN design algorithm for classification problems. Soft Computing, 14, 953-971. https://doi.org/10.1007/s00500-009-0488-z (Original work published)