Evolutionary optimization of fuzzy models with asymmetric RBF membership functions using simplified fitness sharing

Authors:
Min-Soeng Kim;Chang-Hyun Kim;Ju-Jang Lee
Affiliations:
Dept. of Electrical Engineering and Computer Science, KAIST, Taejon, Korea;Dept. of Electrical Engineering and Computer Science, KAIST, Taejon, Korea;Dept. of Electrical Engineering and Computer Science, KAIST, Taejon, Korea
Venue:
IFSA'03 Proceedings of the 10th international fuzzy systems association World Congress conference on Fuzzy sets and systems
Year:
2003

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Abstract

A new evolutionary optimization scheme for designing a Takagi-Sugeno fuzzy model is proposed in this paper. To achieve better modeling performance, asymmetric RBF membership functions are used. Penalty function is proposed and used in the fitness function to prevent overlapping membership functions in the resulting fuzzy model. The simplified fitness sharing scheme is used to enhance the searching capability of the proposed evolutionary optimization algorithm. Some simulations are performed to show the effectiveness of the proposed algorithm.