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A simultaneous method for fuzzy memberships and rule optimization

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3 Author(s)
K. S. Tang ; Dept. of Electron. Eng., City Univ. of Hong Kong, Hong Kong ; C. Y. Chan ; K. F. Man

A new scheme to optimize an optimal fuzzy subsets and rules is proposed. The method is derived by using genetic algorithms where the genes of the chromosome are classified into two types of genes. These genes can be arranged in a hierarchical form and one type of the genes control the other type of genes. The effectiveness of this genetic formulation enables the fuzzy subsets and rules to be optimally reduced and yet, the system performance is well maintained. To justify this approach of fuzzy logic design, the proposed scheme is experimentally demonstrated by applying it to control a constant water pressure pumping system

Published in:

Industrial Technology, 1996. (ICIT '96), Proceedings of The IEEE International Conference on

Date of Conference:

2-6 Dec 1996