文献类型：会议论文

英文题名：Research on Floating Point Representation Genetic Algorithm Based on Wavelet Threshold Shrinkage Denoising

作者：Cui, Mingyi[1];Lu, Junya[1]

第一作者：崔明义

通讯作者：Cui, MY[1]

机构：[1]Henan Univ Finance & Econ, Sch Comp & Informat Engn, Zhengzhou 450002, Peoples R China

第一机构：河南财经政法大学计算机与信息工程学院

通讯机构：[1]corresponding author), Henan Univ Finance & Econ, Sch Comp & Informat Engn, Zhengzhou 450002, Peoples R China.|[1048412]河南财经政法大学计算机与信息工程学院;[10484]河南财经政法大学;

会议论文集：IEEE International Conference on Intelligent Computing and Intelligent Systems

会议日期：NOV 20-22, 2009

会议地点：Shanghai, PEOPLES R CHINA

语种：英文

外文关键词：Genetic Algorithm; Mutation; Shrinkage Denoising; Wavelet Threshold

摘要：Floating point representation (FPR) is of the strongpoint of high precision and facilitating search on high-dimension space It is superior to other representation in function optimization and restriction optimization But, the noise was brought about in run environment of floating point representation genetic algorithm (FPRGA) This was often neglected by researchers Simple FPRGA uses bounded random mutation It cannot avoid the noise to influence on the algorithm performance This paper presents a floating point representation genetic algorithm based on wavelet threshold shrinkage denoising (FGAWSD) A filter was structured Mutation operation was replaced with different thresholds denoising The experiments were done The result of the research and the experiments indicates that the method is reliable in theory, is feasible in technique The precision of the optimal solution of problem can be enhanced with selecting proper threshold The method is of high stability