计算机工程与应用 ›› 2011, Vol. 47 ›› Issue (2): 35-37.DOI: 10.3778/j.issn.1002-8331.2011.02.011

• 研究、探讨 • 上一篇    下一篇

小波分解的浮点数编码遗传算法消噪变异研究

崔明义   

  1. 河南财经学院 信息学院,郑州 450002
  • 收稿日期:2009-02-24 修回日期:2009-04-12 出版日期:2011-01-11 发布日期:2011-01-11
  • 通讯作者: 崔明义

Research on denoising mutation of FPRGA based on wavelet decomposition

CUI Mingyi   

  1. School of Information,Henan University of Finance & Economics,Zhengzhou 450002,China
  • Received:2009-02-24 Revised:2009-04-12 Online:2011-01-11 Published:2011-01-11
  • Contact: CUI Mingyi

摘要: 遗传算法的应用领域越来越广泛,其编码问题是遗传算法研究的难点之一。浮点数编码具有精度高、便于大空间搜索的优点,在函数优化和约束优化中明显优于其他编码,但浮点数编码在遗传环境中产生的“噪音”和对算法性能的影响,常常被人们所忽视。基于小波分解原理,将“噪音”映射到Haar小波基上,对算法消噪变异,并编程予以实现。研究及实验结果表明,这种方法明显优于其他算法,在理论上是可靠的,技术上是可行的。

关键词: 小波分解, 浮点数编码, 遗传算法, 消噪变异

Abstract: Genetic algorithm(GA) is used widely to many fields.Coding is one of difficult issues of GA research.Floating Point Presentation(FPR) is of the advantage of higher precision and convenience of searching in great space.FPR is superior to other codes in function optimization and restriction optimization.But the noises are neglected by researches which are generated by FPR in genetic environment.Basing on wavelet decomposition,the noises are mapped to Haar basis,algorithm is made with denoising mutation,the algorithm is implemented by programming.The results of the research and the experiments indicate the method is superior to other algorithms,is reliable in theory,is feasible in technique.

Key words: wavelet decomposition, Floating Point Representation(FPR), Genetic Algorithm(GA), denoising mutation

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