A Clustering-based Algorithm to Extracting Fuzzy Rules for System Modeling

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題名:	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
貢獻者:	淡江大學電機工程學系
關鍵詞:	Clustering-Based Algorithm;Fuzzy Inference System;System Modeling
日期:	2011-12
上傳時間:	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
顯示於類別:	[電機工程學系暨研究所] 期刊論文

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