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    National Tsing Hua University Institutional Repository > 電機資訊學院 > 資訊工程學系 > 期刊論文 >  ANFIS: Adaptive-Network-Based Fuzzy Inference Systems


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/12643


    Title: ANFIS: Adaptive-Network-Based Fuzzy Inference Systems
    Authors: Jang, J.-S.R.
    Date: 1993
    Publisher: Institute of Electrical and Electronics Engineers Inc
    Keywords: fuzzy logic
    inference mechanisms
    knowledge based systems
    neural nets
    signal processing
    time series
    Non-controlled Indexing
    Abstract: The architecture and learning procedure underlying ANFIS (adaptive-network-based fuzzy inference system) is presented, which is a fuzzy inference system implemented in the framework of adaptive networks. By using a hybrid learning procedure, the proposed ANFIS can construct an input-output mapping based on both human knowledge (in the form of fuzzy if-then rules) and stipulated input-output data pairs. In the simulation, the ANFIS architecture is employed to model nonlinear functions, identify nonlinear components on-line in a control system, and predict a chaotic time series, all yielding remarkable results. Comparisons with artificial neural networks and earlier work on fuzzy modeling are listed and discussed. Other extensions of the proposed ANFIS and promising applications to automatic control and signal processing are also suggested.
    Relation Link: http://webservices.ieee.org/pindex_basic.html
    URI: http://nthur.lib.nthu.edu.tw/handle/987654321/12643
    Appears in Collections:[資訊工程學系] 期刊論文
    [資訊系統與應用研究所] 期刊論文
    [電腦與通訊科技研發中心] 期刊論文

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