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    jsp.display-item.identifier=請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/75246

    题名: A Clustering-based Algorithm to Extracting Fuzzy Rules for System Modeling
    作者: Chen, Ching-Yi;Li, Shin-An;Liu, Ta-Kang;Chen, Kuang-Yuan;Wong, Ching-Chang
    贡献者: 淡江大學電機工程學系
    关键词: Clustering-Based Algorithm;Fuzzy Inference System;System Modeling
    日期: 2011-12
    上传时间: 2012-03-16 16:31:01 (UTC+8)
    出版者: Korea: Advanced Institute of Convergence IT
    摘要: In this paper, a clustering-based algorithm is proposed for automatically constructing a multi-input fuzzy model where only the input-output data of the identified system are available. The proposed clustering method can automatically yield the number of clusters and its associated cluster centers from the input training data. While the features of training data are extracted by the proposed clustering method, the valuable information on the initial structure of the Sugeno-type fuzzy inference system is built up. For testing the performance of the proposed system modeling method, two wellknow examples from the literature and one real-world data set from the Taiwan's stock market are used to illustrate the validity of the proposed fuzzy system design procedure.
    關聯: International Journal of Advancements in Computing Technology 3(11), pp.394-401
    显示于类别:[電機工程學系暨研究所] 期刊論文


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