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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46250


    Title: A GA-based method for constructing fuzzy systems directly from numerical data
    Authors: 翁慶昌;Wong, Ching-chang;Chen, Chia-chong
    Contributors: 淡江大學電機工程學系
    Date: 2000-12
    Issue Date: 2010-03-26 21:37:29 (UTC+8)
    Publisher: Piscataway: Institute of Electrical and Electronics Engineers (IEEE)
    Abstract: A method based on the concepts of genetic algorithm (GA) and recursive least-squares method is proposed to construct a fuzzy system directly from some gathered input-output data of the discussed problem. The proposed method can find an appropriate fuzzy system with a low number of rules to approach an identified system under the condition that the constructed fuzzy system must satisfy a predetermined acceptable performance. In this method, each individual in the population is constructed to determine the number of fuzzy rules and the premise part of the fuzzy system, and the recursive least-squares method is used to determine the consequent part of the constructed fuzzy system described by this individual. Finally, three identification problems of nonlinear systems are utilized to illustrate the effectiveness of the proposed method.
    Relation: IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 30(6), pp.904-911
    DOI: 10.1109/3477.891153
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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