English  |  正體中文  |  简体中文  |  Items with full text/Total items : 60695/93562 (65%)
Visitors : 1051671      Online Users : 24
RC Version 7.0 © Powered By DSPACE, MIT. Enhanced by NTU Library & TKU Library IR team.
Scope Tips:
  • please add "double quotation mark" for query phrases to get precise results
  • please goto advance search for comprehansive author search
  • Adv. Search
    HomeLoginUploadHelpAboutAdminister Goto mobile version
    Please use this identifier to cite or link to this item: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/75246

    Title: A Clustering-based Algorithm to Extracting Fuzzy Rules for System Modeling
    Authors: Chen, Ching-Yi;Li, Shin-An;Liu, Ta-Kang;Chen, Kuang-Yuan;Wong, Ching-Chang
    Contributors: 淡江大學電機工程學系
    Keywords: Clustering-Based Algorithm;Fuzzy Inference System;System Modeling
    Date: 2011-12
    Issue Date: 2012-03-16 16:31:01 (UTC+8)
    Publisher: Korea: Advanced Institute of Convergence IT
    Abstract: 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.
    Relation: International Journal of Advancements in Computing Technology 3(11), pp.394-401
    Appears in Collections:[電機工程學系暨研究所] 期刊論文

    Files in This Item:

    File Description SizeFormat

    All items in 機構典藏 are protected by copyright, with all rights reserved.

    DSpace Software Copyright © 2002-2004  MIT &  Hewlett-Packard  /   Enhanced by   NTU Library & TKU Library IR teams. Copyright ©   - Feedback