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    何宏, 钱锋. 基于免疫网络理论的动态超变异免疫算法[J]. 华东理工大学学报(自然科学版), 2007, (3): 429-435.
    引用本文: 何宏, 钱锋. 基于免疫网络理论的动态超变异免疫算法[J]. 华东理工大学学报(自然科学版), 2007, (3): 429-435.
    HE Hong, QIAN Feng. Dynamic Hypermutation Immune Algorithms Based on Immune Network Theory[J]. Journal of East China University of Science and Technology, 2007, (3): 429-435.
    Citation: HE Hong, QIAN Feng. Dynamic Hypermutation Immune Algorithms Based on Immune Network Theory[J]. Journal of East China University of Science and Technology, 2007, (3): 429-435.

    基于免疫网络理论的动态超变异免疫算法

    Dynamic Hypermutation Immune Algorithms Based on Immune Network Theory

    • 摘要: 基于免疫网络理论,提出了一种动态超变异免疫算法,该算法通过采用新的超变异方法增强了算法在解域的搜索能力。同时根据抗体的激励水平进行免疫调节操作,保持了抗体群的多样性。最后根据随机过程的理论知识,证明了该算法的收敛性。仿真结果表明:该算法采用格雷编码时的性能优于用二进制编码实现的算法,与遗传算法和克隆选择算法相比,不仅收敛速度快,而且全局搜索能力强。

       

      Abstract: A new dynamic hypermutation immune algorithm(DHIA) is proposed on the basis of (immune) network theory.DHIA adopts novel hypermutation operation to further strengthen the searching(ability) of the algorithm in the solution domain.Immune regulatory operation based on the stimulation level of each antibody is also applied to effectively maintain the diversity of the population and avoid the premature convergence.Furthermore,the convergence of the DHIA is proved theoretically through the Markov stochastic proc...

       

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