Generating Of Fuzzy Rule from Examples for Fuzzy Control System by Using Genetic Algorithms Real Code
published by Aِl-Baath University
in 2014
in
and research's language is
العربية
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Abstract in English
One of the principal applications of fuzzy logic is in control system design. Fuzzy logic controllers (FLC) can be used to control
systems where the use of conventional control techniques may be Problematic. The tuning of fuzzy controllers has tended to rely on human expert knowledge, but where the number of rules and fuzzy sets is large. The Problem of generation desirable fuzzy rule is very important in the development of fuzzy systems. The purpose of this paper is to present a generation method of fuzzy control rules by learning from examples using genetic algorithms (GA). We propose real coded genetic algorithms (RCGA) for learning fuzzy rules, and an iterative process for obtaining set of rules which covers the examples set with a covering value previously defined.
References used
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