Cooperation between the inference system and the rule base by using multiobjective genetic algorithms

Marquez A.A. Márquez F.A. Peregrín A.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Doi 10.1007/978-3-540-87656-4_91
Volumen 5271 LNAI páginas 739 - 746
2008-12-01
Citas: 8
Abstract
This paper presents an evolutionary Multiobjective learning model achieving positive synergy between the Inference System and the Rule Base in order to obtain simpler and still accurate linguistic fuzzy models by learning fuzzy inference operators and applying rule selection. The Fuzzy Rule Based Systems obtained in this way, have a better trade-off between interpretability and accuracy in linguistic fuzzy modeling applications. © 2008 Springer-Verlag.
Adaptive defuzzification, Adaptive inference system, Interpretability-accuracy trade-off, Linguistic fuzzy modeling, Multiobjective genetic algorithms, Rule selection
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