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Building a Fuzzy Model with Transparent Membership Functions through Constrained Evolutionary Optimization

Min-Soeng Kim, Chang-Hyun Kim, and Ju-Jang Lee
International Journal of Control, Automation, and Systems, vol. 2, no. 3, pp.298-309, 2004

Abstract : In this paper, a new evolutionary scheme to design a TSK fuzzy model from relevant data is proposed. The identification of the antecedent rule parameters is performed via the evolutionary algorithm with the unique fitness function and the various evolutionary operators, while the identification of the consequent parameters is done using the least square method. The occurrence of the multiple overlapping membership functions, which is a typical feature of unconstrained optimization, is resolved with the help of the proposed fitness function. The proposed algorithm can generate a fuzzy model with transparent membership functions. Through simulations on various problems, the proposed algorithm found a TSK fuzzy model with better accuracy than those found in previous works with transparent partition of input space.

Keyword : : Evolutionary algorithm, model interpretability, Takagi-Sugeno-Kang fuzzy model, time series prediction

 
 
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