Automatic fuzzy rules generation using fuzzy genetic algorithm

Authors:
Huai-xiang Zhang;Bo Zhang;Feng Wang
Affiliations:
Institute of Computer Application, Hangzhou Dianzi University, Hangzhou, Zhejiang, China;Institute of Computer Application, Hangzhou Dianzi University, Hangzhou, Zhejiang, China;Institute of Computer Application, Hangzhou Dianzi University, Hangzhou, Zhejiang, China
Venue:
FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6
Year:
2009

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Abstract

To solve the problem which is hard to avoid the local optimal solution or slower population diversity when using genetic algorithm to generate the fuzzy rules in a fuzzy system, this paper proposes an automatic rule generation using fuzzy genetic algorithm. This algorithm utilizes the rules population diversity and evolutionary speed to automatically adjust the crossover rate and mutation rate based on fuzzy logic, which leads to the automatic control rules generation of a genetic fuzzy system. In addition, the performance indices of control system and how to evaluate the fitness function in genetic algorithm are also presented. Finally, simulation results demonstrate the proposed algorithm is practical and effective in applications.