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Author Katebi, S. D.en_US
Available date 2009-11-25T13:06:24Zen_US
Publication Date 1996en_US
Publication Name Engineering Journal of Qatar University
Citation Engineering Journal of Qatar University, 1996, Vol. 9, Pages 147-169.en_US
URI http://hdl.handle.net/10576/7978en_US
Abstract In this paper modeling, selection and optimization of fuzzy rules for multivariable feedback process control and decision making systems are developed and discussed. A general model for multivariable fuzzy rules is derived and sets of fuzzy parameters are assigned to the consequents of each rule. A genetic algorithm is used to optimize these parameters. A genetic algorithm search technique is also developed for the selection of the sub-set of appropriate rules from a larger theoretically possible set. The procedure is implemented on a multivariable dynamic model and results of extensive simulation studies are presented to demonstrate a satisfactory performance of the proposed approachen_US
Language enen_US
Publisher Qatar Universityen_US
Subject Engineering: Research & Technologyen_US
Title Selection Of Optimized Fuzzy Rules For Process Control Systems: Using Genetic Algorithmsen_US
Type Articleen_US
Pagination 147-169en_US
Volume Number 9en_US


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