TUNG FANG Institutional Repository:Item 987654321/1471
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    題名: Festure-Extraction-Based Neuron-Fuzzy Classification Model
    作者: Guo, Nai Ren
    Kuo, Chao-Lin
    Tsai, Tzong-Jiy
    蔡宗吉
    (東方技術學院電機工程系)
    貢獻者: 東方技術學院電機工程系
    關鍵詞: Fuzzy set
    neural networks
    classification problem
    日期: 2008-12-20
    上傳時間: 2012-12-24 15:54:07 (UTC+8)
    摘要: In this paper, a neuron-fuzzy classification model (NFCM) is proposed that enables the extraction the feature variable and infers the classification results. The NFCM automatically generates the rules from the numerical data and triangular functions are used as the membership functions both in the feature extraction unit and the inference unit. To improve the proposed NFCM, one modificatory algorithm is applied. We utilize the Evolutionary Programming (EP) to determine the distribution of the fuzzy sets for each feature variable of the feature extraction unit. Finally, the proposed NFCM has been validated using one benchmark data set that is the Wine database.
    關聯: The 16th Natinal Conference on Fuzzy Theory and Its Applications, pp.591-596
    中華民國第16屆模糊理論及其應用研討會會議手冊
    模糊理論及其應用研討會
    顯示於類別:[電機工程系(數位科技系、玩具科)] 國科會計畫

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