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结合混沌和抗体克隆选择学说,提出一种新的人工免疫系统算法——自适应混沌克隆进化规划算法.新算法基于Logistic混沌序列;利用个体质量、进化代数和个体分布情况构造混沌变异算子;通过Logistic混沌序列自适应调整变异尺度.理论分析和仿真实验表明,与标准的遗传算法和采用随机变异的克隆选择算法相比,该算法收敛速度快,求解精度高,稳定性好,并有效抑制了早熟现象.
Combining the theory of chaos and antibody clonal selection, a new artificial immune system algorithm - adaptive chaotic clonal evolutionary programming is proposed. The new algorithm is based on Logistic chaotic sequence; the chaos mutation operator is constructed by using individual mass, evolutionary algebra and individual distribution; The chaos sequence of Logistic adaptively adjusts the variation scale.The theoretical analysis and simulation results show that compared with the standard genetic algorithm and the clonal selection algorithm using random variation, the proposed algorithm has the advantages of fast convergence rate, high solution accuracy, good stability and effective suppression Premature phenomenon.