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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/46412


    Title: A grey-based clustering algorithm and its application on fuzzy system design
    Authors: 翁慶昌;Wong, Ching-chang;Lai, Hung-ren
    Contributors: 淡江大學電機工程學系
    Date: 2003-03
    Issue Date: 2010-03-26 22:16:36 (UTC+8)
    Publisher: Taylor & Francis
    Abstract: A grey-based clustering method was proposed and applied on fuzzy system design. A new grey-clustering algorithm using grey relational analysis as the similarity measure was developed for data clustering. It was more effective and accurate than C-Means like algorithms when dealing with data clustering issue, when the compact and complete separate data were considered. Some data clustering examples are presented to illustrate the effectiveness of the proposed clustering algorithm. Next, an application of the proposed method on fuzzy system design is presented. The procedure of fuzzy system design can be separated into two parts. In the first procedure, the grey-clustering algorithm was employed to form a rough fuzzy system only from gathered input-output data. Then, the gradient descent method was used to determine a suitable parameter set of the formed fuzzy system. A nonlinear system modelling and an inverted pendulum control problem were then used to illustrate the validity of the proposed fuzzy system design procedure.
    Relation: International Journal of Systems Science 34(4), pp.269-281
    DOI: 10.1080/0020772031000158519
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

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