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Adaptive chaos clonal evolutionary programming algorithm

机译:自适应混沌克隆进化规划算法

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Based on the chaos movement and the clonal selection theory, a novel artificial immune system algorithm, Adaptive Chaos Clonal Evolutionary Programming Algorithm (ACCEP), is proposed in this paper. The new algorithm uses the Logistic Sequence to control the mutation scale and uses the Chaos Mutation Operator to control the clonal selection. Compared with SGA and Clonal Selection Algorithm, ACCEP can enhance the precision and stability, avoid prematurity to some extent, and have the high convergence speed. The results of the experiment indicate that ACCEP has the capability to solve complex machine learning tasks, like Multimodal Function Optimization.
机译:基于混沌运动和克隆选择理论,提出了一种新型的人工免疫系统算法,即自适应混沌克隆进化规划算法(ACCEP)。新算法使用Logistic序列来控制突变规模,并使用混沌突变算子来控制克隆选择。与SGA和克隆选择算法相比,ACCEP可以提高精度和稳定性,在一定程度上避免过早出现,并且具有较高的收敛速度。实验结果表明,ACCEP具有解决复杂机器学习任务的能力,例如多峰函数优化。

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