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ju you pbest yin dao ji zhi de shi ying xing duo ce lue cha fen jin hua suan fa
Author(s): 
Pages: 711-721
Year: Issue:  8
Journal: Pattern Recognition and Artificial Intelligence

Keyword:  Differential Evolution AlgorithmLogistic Chaotic SystemGuiding Scheme of PbestMultiple Differential Mutation StrategyShifted and Rotated Functions;
Abstract: 为进一步提升差分进化算法的收敛性能,提出一种具有Pbest引导机制的适应性多策略差分进化算法(AMSDE).AMSDE设计交叉概率控制参数库、变异尺度参数库及差分变异策略库,其中,交叉概率采用Logistic混沌序列来模拟,尺度参数采用线性变化机制产生,差分变异策略库采用6个常用的差分变异策略组成,并给出算法运行的框架.最后,基于25个标准测试函数的仿真结果表明,AMSDE的收敛性能优于现存的其它差分进化算法,具有较好的收敛精度及收敛速度.
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