文献类型：会议论文

英文题名：An Improved Float-Coded Genetic Algorithm Based on Wavelet Denoising Mutation

作者：Cui, Mingyi

第一作者：崔明义

通讯作者：Cui, MY[1]

机构：[1]Henan Univ Finance & Econ, Sch Informat, 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 Informat, 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：7th World Congress on Intelligent Control and Automation

会议日期：JUN 25-27, 2008

会议地点：Chongqing, PEOPLES R CHINA

语种：英文

外文关键词：Denoising Mutation; Float Code; Genetic Algorithm; Wavelet

摘要：Coding is an important and a difficult subject of research on genetic algorithm (GA). Float Code (FC) is super to other codes in use. But, noise and its influence on GA performance were ignored by researches in genetic operation. Mutation played an important role of improving GA performance. This paper presents a float-coded genetic algorithm (FCGA) with wavelet denoising mutation. They are called the bound crossover and wavelet denoising mutation. By introducing the proposed genetic operation, both the solution quality and stability are better than GA with conventional genetic operations. Decomposing of FC noise was proved with wavelet in theory. FC denoising mutation was implemented in it. Experiments were made in it. The results of the research and experiments indicate that the theory is credible and the method is feasible in it. FCGA is of active significance to extend application space of GA.