Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2011). A double axis classi. Presentado en.
Francisco Herrera Triguero
First name
Francisco
Last name
Herrera Triguero
2011
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2011). A Double Axis Classification of Interpretability Measures for Linguistic Fuzzy Rule-Based Systems (A. M. Fanelli, W. Pedrycz, & A. Petrosino, Eds.). Berlin, Heidelberg: Springer Berlin Heidelberg.
Alcalá, R., Gacto, M. J., & Herrera Triguero, F. (2011). A Fast and Scalable Multi-Objective Genetic Fuzzy System for Linguistic Fuzzy Modeling in High-Dimensional Regression Problems. IEEE Transactions on Fuzzy Systems, 19, 666-681. https://doi.org/10.1109/TFUZZ.2011.2131657
Sanz, J., Fernández Hilario, A. L., Bustince, H., & Herrera Triguero, F. (2011). A Genetic Tuning to Improve the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets: Degree of Ignorance and Lateral Position. International Journal of Approximate Reasoning, 52, 751-766. https://doi.org/10.1016/j.ijar.2011.0
2010
Fernández Hilario, A. L., del Jesus Díaz, M. J., & Herrera Triguero, F. (2010). Analysing the Hierarchical Fuzzy Rule Based Classification Systems with Genetic Rule Selection. 69-74. Mieres (Spain). (Original work published 2026)
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2010). 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. 228-238. Córdoba. (Original work published 2026)
Fernández Hilario, A. L., Luengo, J., García López, S., Bernadó-Mansilla, E., & Herrera Triguero, F. (2010). Genetics-Based Machine Learning for Rule Induction: State of the Art, Taxonomy and Comparative Study. IEEE Transactions on Evolutionary Computation, 14, 913-941. https://doi.org/10.1109/TEVC.2009.2039140
Berlanga, F., Rivera Rivas, A. J., del Jesus Díaz, M. J., & Herrera Triguero, F. (2010). GP-COACH: Genetic Programming-based learning of Compact and ACcurate fuzzy rule-based classification systems for High-dimensional problems. Information Sciences, 180, 1183-1200. https://doi.org/10.1016/j.ins.2009.12.020
Sanz, J., Fernández Hilario, A. L., Bustince, H., & Herrera Triguero, F. (2010). Improving the Performance of Fuzzy Rule-Based Classification Systems with Interval-Valued Fuzzy Sets and Genetic Amplitude Tuning. Information Sciences, 180, 3674-3685. https://doi.org/10.1016/j.ins.2010.06.018
Gacto, M. J., Alcalá, R., & Herrera Triguero, F. (2010). Indice de Interpretabilidad Semántica para el Ajuste de Sistemas Basados en Reglas Difusas y Selección de Reglas Mediante un Algoritmo Evolutivo Multi-Objetivo. 73-78. Huelva. (Original work published 2026)