Fuzzy rule-based systems

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
Palacios, A. M., Martínez, A., Sánchez, L., & Couso, I. (2015). Sequential pattern mining applied to aeroengine condition monitoring with uncertain health data. Engineering Applications of Artificial Intelligence, 44, 10-24. https://doi.org/10.1016/j.engappai.2015.05.003
Sánchez, L., Otero, J., Couso, I., & Blanco, C. (2016). Battery diagnosis for electrical vehicles through semi-physical fuzzy models. 416-423. https://doi.org/10.1109/FUZZ-IEEE.2016.7737717 (Original work published 2026)
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
Casillas, J., Cordón García, Ó., Herrera Triguero, F., & del Jesus Díaz, M. J. (2001). Genetic tuning of fuzzy rule-based systems integrating linguistic hedges. 3, 1570-1574. https://doi.org/10.1109/NAFIPS.2001.943783 (Original work published 2026)