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    National Tsing Hua University Institutional Repository > 科技管理學院  > 服務科學研究所 > 期刊論文 >  Active training of backpropagation neural networks using the learning by experimentation methodology


    Please use this identifier to cite or link to this item: http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/84795


    Title: Active training of backpropagation neural networks using the learning by experimentation methodology
    Authors: Lin FR;Shaw MJ
    教師: 林福仁
    Date: 1997
    Publisher: Springer Verlag
    Relation: ANNALS OF OPERATIONS RESEARCH, Springer Verlag, Volume 75, Number 0, Pages 105-122,1997
    Keywords: neural networks
    Learning by Experimentation Methodology
    active learning
    Abstract: This paper proposes the Learning by Experimentation Methodology (LEM) to facilitate the active training of neural networks. In an active learning paradigm, a learning mechanism can actively interact with its environment to acquire new knowledge and revise itself. The learning by experimentation is an active learning strategy. Experiments are conducted to form hypotheses, and the evaluation of those hypotheses feeds back to the learning mechanism to revise knowledge. We use a backpropagation neural network as the learning mechanism. We also adopt a weight space analysis method and a heuristic to select salient attributes to perform new experiments in order to revise the network. Finally we illustrate performance by solving the sonar signal classification problem.
    URI: http:/dx.doi.org/10.1023/A:1018999110972
    http://www.springerlink.com/
    http://nthur.lib.nthu.edu.tw/dspace/handle/987654321/84795
    Appears in Collections:[服務科學研究所] 期刊論文
    [高階經營管理碩士在職專班] 期刊論文

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