混沌协方差矩阵自适应进化策略优化算法

doi:10.13229/j.cnki.jdxbgxb201703034

摘要/Abstract

摘要： 为了改进进化策略算法的性能,提出了一种混沌协方差矩阵自适应进化策略(Chaos-CMA-ES)算法,该算法在协方差矩阵自适应进化策略(CMA-ES)算法的基础上引入了混沌算子,并利用其更新种群中心的位置,使得种群具备良好的全局搜索能力。试验结果表明,本文算法对复杂多峰函数的寻优效果好于其他几种算法。最后,将本文算法用于优化网络安全态势的预测模型,预测结果的精度高于其他方法。

关键词: 人工智能, 优化算法, 协方差矩阵自适应进化策略, 混沌优化, 网络安全态势预测

Abstract: A Chaos Covariance Matrix Adaptation Evolution Strategy (Chaos-CMA-ES) optimization algorithm is proposed. The Chaos-CMA-ES algorithm uses the chaos operator to update the mean of the population on the basis of the original CMA-ES algorithm. Chaos-CMA-ES algorithm has good global search capability by using the improved operation. The comparative experimental results verify that the Chaos-CMA-ES algorithm has better optimization effect than other optimization algorithms for complex multimodal function. A case study of the network security situation prediction is examined to demonstrate the ability and applicability of the Chaos-CMA-ES algorithm. The prediction accuracy is higher than other methods.

Key words: artificial intelligence, optimization algorithm, covariance matrix adaptation evolution strategy(CMA-ES), chaos optimization, network security situation prediction

中图分类号:

TP18

胡冠宇, 乔佩利. 混沌协方差矩阵自适应进化策略优化算法[J]. 吉林大学学报(工学版), 2017, 47(3): 937-943.

HU Guan-yu, QIAO Pei-li. Chaos covariance matrix adaptation evolution strategy optimization algorithm[J]. 吉林大学学报(工学版), 2017, 47(3): 937-943.

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