A learning process for fuzzy control rules using genetic algorithms

نویسندگان

Francisco Herrera

Manuel Lozano

José L. Verdegay

چکیده

The purpose of this paper is to present a genetic learning process for learning fuzzy control roles 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 kinds 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 leaming process are developed formulating suitable genetic algorithms. @ 1998 Elsevier Science B.V. All rights reserved

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