A LEARNING-PROCESS FOR FUZZY CONTROL RULES USING GENETIC ALGORITHMS

Authors
HERRERA F LOZANO M VERDEGAY JL
Citation
F. Herrera et al., A LEARNING-PROCESS FOR FUZZY CONTROL RULES USING GENETIC ALGORITHMS, Fuzzy sets and systems, 100(1-3), 1998, pp. 143-158
Citations number
32
Categorie Soggetti
Statistic & Probability",Mathematics,"Computer Science Theory & Methods","Statistic & Probability",Mathematics,"Computer Science Theory & Methods
Journal title
Fuzzy sets and systems → ACNP
ISSN journal
01650114
Volume
100
Issue
1-3
Year of publication
1998
Pages
143 - 158
Database
ISI
SICI code
0165-0114(1998)100:1-3<143:ALFFCR>2.0.ZU;2-W
Abstract
The purpose of this paper is to present a genetic learning process for learning fuzzy control rules from examples. It is developed in three stages: the first one is a fuzzy rule genetic generating process based on a rule learning iterative approach, the second one combines two ki nds of rules, experts rules if there are and the previously generated fuzzy control rules, removing the redundant fuzzy rules, and the third one is a tuning process for adjusting the membership functions of the fuzzy rules. The three components of the learning process are develop ed formulating suitable genetic algorithms. (C) 1998 Elsevier Science B.V. All rights reserved.