淡江大學機構典藏:Item 987654321/46421
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    题名: A clustering-based method for fuzzy modeling
    作者: 翁慶昌;Wong, Ching-chang;Chen, Chia-chong
    贡献者: 淡江大學電機工程學系
    日期: 1999-06
    上传时间: 2010-03-26 22:17:41 (UTC+8)
    出版者: Institute of Electronics, Information and Communication Engineers (IEICE)
    摘要: In this paper, a clustering-based method is proposed for automatically constructing a multi-input Takagi-Sugeno (TS) fuzzy model where only the input-output data of the identified system are available. The TS fuzzy model is automatically generated by the process of structure identification and parameter identification. In the structure identification step, a clustering method is proposed to provide a systematic procedure to partition the input space so that the number of fuzzy rules and the shapes of fuzzy sets in the premise part are determined from the given input-output data. In the parameter identification step, the recursive least-squares algorithm is applied to choose the parameter values in the consequent part from the given input-output data. Finally, two examples are used to illustrate the effectiveness of the proposed method.
    關聯: IEICE transactions on information and systems E82-D(6), pp.1058-1065
    显示于类别:[電機工程學系暨研究所] 期刊論文

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