RT Conference Proceedings
T1 Rule base and inference system cooperative learning of mamdani fuzzy systems with multiobjective genetic algorithms
A1 Márquez Hernández, Antonio Ángel
A1 Márquez Hernández, Francisco Alfredo
A1 Peregrín Rubio, Antonio
K1 Sistemas difusos
AB In this paper, we present an evolutionary multiobjectivelearning model achieving positive synergy between the InferenceSystem and the Rule Base in order to obtain simpler, more compactand still accurate linguistic fuzzy models by learning fuzzy inferenceoperators together with Rule Base. The Multiobjective EvolutionaryAlgorithm proposed generates a set of Fuzzy Rule Based Systemswith different trade-offs between interpretability and accuracy inlinguistic fuzzy modeling, allowing the designers select the one thatinvolves the most adequate equilibrium for the desired application.
PB European Society of Fuzzy Logic and Technology
SN 978-989-95079-6-8
YR 2009
FD 2009
LK http://hdl.handle.net/10272/6293
UL http://hdl.handle.net/10272/6293
LA eng
NO Márquez Hernández, A.A., Márquez Hernández, F.A., Peregrín Rubio, A.: "Rule base and inference system cooperative learning of mamdani fuzzy systems with multiobjective genetic algorithms". En: Proceedings of the Joint 2009 International Fuzzy Systems Association World Congress and 2009 European Society of Fuzzy Logic and Technology Conference, Lisbon, Portugal, July 20-24, 2009
DS Repositorio Institucional de la Universidad de Huelva
RD 13 jul 2026