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    請使用永久網址來引用或連結此文件: https://tkuir.lib.tku.edu.tw/dspace/handle/987654321/68571

    題名: Fuzzy regression with radial basis function network
    作者: 鄭啟斌;Lee, E. S.
    貢獻者: 淡江大學資訊管理學系
    關鍵詞: Regression analysis;Nonparametric fuzzy regression;Fuzzy radial basis network
    日期: 2001-09-28
    上傳時間: 2011-10-23 13:17:07 (UTC+8)
    摘要: Radial basis function network is used in fuzzy regression analysis without predefined functional relationship between the input and the output. The proposed approach is a fuzzification of the connection weights between the hidden and the output layers. This fuzzy network is trained by a hybrid learning algorithm, where self-organized learning is used for training the parameters of the hidden units and supervised learning is used for updating the weights between the hidden and the output layers. The c-mean clustering method and the k-nearest-neighbor heuristics are used for the self-organized learning. The supervised learning is carried out by solving a linear possibilistic programming problem. Techniques for the generalization of the network are also proposed. Numerical examples are used to illustrate and to test the performances of the approach.
    關聯: Fuzzy Sets and Systems 119, pp.291-301
    DOI: 10.1016/S0165-0114(99)00098-6
    顯示於類別:[資訊管理學系暨研究所] 期刊論文


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