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    Please use this identifier to cite or link to this item: http://asiair.asia.edu.tw/ir/handle/310904400/8103

    Title: A Genetic Algorithm with Adaptive Mutations and Family Competition for Training Neural Network
    Authors: Y-M Yang;J-T Horng;C-Y Kao
    Contributors: Department of Bioinformatics
    Keywords: Genetic Algorithm;Ant Colony Optimization
    Date: 2000
    Issue Date: 2010-03-19 16:24:08 (UTC+8)
    Publisher: Asia University
    Abstract: This paper Proposes a novel adaptive genetic algorithm (GA) extrapolated by an ant colony optimization. We first prove that the algorithm converges to the unique global optimal solution with probability arbitrarily close to one and then, by experimental studies, show that the algorithm converges faster to the optimal solution than GA with elitism and the population average fitness value also converges to the optimal fitness value. We further discuss controlling the tradeoff of exploration and exploitation by a parameter associated with the proposed algorithm.
    Relation: International Journal of Neural Systems 10 (5): 333-352
    Appears in Collections:[生物資訊與醫學工程學系 ] 期刊論文

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