GFMRA的浮点数编码消噪变异  

Floating point representation denoising mutation on GFMRA

作　　者：崔明义[1] 

机构地区：[1]河南财经政法大学计算机与信息工程学院,郑州450002

出　　处：《计算机工程与应用》2014年第20期15-19,共5页Computer Engineering and Applications

基　　金：国家自然科学基金(No.61202285);河南省科技攻关项目(No.132102210138)

摘　　要：MRA是构造小波的重要方法,而GFMRA可以构造任何具有单一母波的正交小波。浮点数编码在函数优化和约束优化领域明显有效于其他编码,但浮点数编码在遗传操作环境中产生的"噪音"严重地影响着遗传算法的性能。在理论分析的基础上,提出基于GFMRA构造的正交小波对浮点数编码消噪变异的FPRGAG方法,并进行了实验。理论研究和实验结果表明,无论是收敛速度还是收敛精度,FPRGAG都远远优于传统算法。该方法理论上是可靠的,技术上是可行的。Multiresolution Analysis（MRA）is an important method of constructing wavelet. Generalized Frame Multire-solution Analysis（GFMRA）can construct any orthonormal wavelet based on single mother function. Floating Point Representation（FPR）is superior to other representation in function optimization and restriction optimization. The noise which FPR brings about influences badly the performance of genetic algorithm in genetic operation environment. This paper is dependent on theoretical analysis. It presents Floating Point Repreaentation Genetic Algorithm （FPRGA） based on GFMRA（FPRGAG）. FPRGAG is a method of FPR denoising mutation by orthonormal wavelet. The experiments are made on FPRGAG. The results of the theoretical research and the experiments indicate FPRGAG is superior to other used algorithms, in convergence efficiency and precision. The method is reliable in theory, is feasible in technique.

关 键 词：广义框架多分辨率分析(GFMRA) 正交小波 浮点数编码 消噪变异 

分 类 号：TP393[自动化与计算机技术—计算机应用技术]