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2-Adic MRA的浮点数编码遗传算法 被引量：2

2-Adic MRA based floating point representation Genetic Algorithm
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摘要 通过2-Adic多分辨率分析,构造正交小波基;证明所构造正交小波用于浮点数编码消噪的正确性;提出用正交小波在浮点数编码遗传算法中进行消噪变异操作,以消除浮点数编码在遗传环境中所产生的噪音对算法性能的影响;构建基于2-Adic多分辨率分析的遗传算法,并进行了实验。仿真实验表明,提出的算法可明显提高浮点数编码遗传算法的收敛速度和精度,具有较高的可靠性。 An orthonormal wavelet basis is constructed with 2-Adic multiresolution analysis. Validity of the constructed orthonormal wavelet is proven in denoising on Floating Point Representation Genetic Algorithm（FPRGA）. Denoising mutation operation with the orthonormal wavelet is proposed in FPRGA. The aim is to remove noises from floating point representation in genetic environment. The genetic algorithm based on 2-Adic multiresolution analysis is structured. The experiment is done. The simulation experiment indicates that the algorithm can improve obviously convergence rate and precision of FPRGA. It has greater reliability than base algorithm.
作者 崔明义
机构地区 河南财经政法大学计算机与信息工程学院 郑州成功财经学院信息工程系
出处 《计算机工程与应用》 CSCD 北大核心 2015年第15期12-16,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)
关键词 2-Adic多分辨率分析(MRA) 正交小波 浮点数编码 消噪变异 遗传算法 2-Adic Multiresolution Analysis（MRA） orthonormal wavelet floating point representation denoising mutation Genetic Algorithm（GA）
分类号 TP301.6 [自动化与计算机技术—计算机系统结构]
  • 相关文献

参考文献15

  • 1Cui Mingyi,Shangguan Yanli.Research on float-coded genetic algorithm based on wavelet denoising mutation[C]//Proceedings of the 3rd International Conference on Natural Computation(ICNC 2007),2007,3:804-809.
  • 2Eshelman L,Schaffer J.Real-coded genetic algorithms and interval schemata[M]//Whitley L.Foundations of Genetic Algorithms.San Francisco:Morgan Kaufmann Publishers,1993,2:187-202.
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  • 7Cui Mingyi.An improved float-coded genetic algorithm based on wavelet denoising mutation[C]//The 7th World Congress on Intelligent Control and Automation(WCICA2008),2008.
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二级参考文献13

  • 1ESHELMAN L,SCHAFFER J.Real-coded genetic algorithms and interval schemata[M].San Francisco:Morgan Kaufmann Publishers,1993:187-202.
  • 2McCORMICK W T,SCHWEITZER P J,WHITE T W.Problem decomposition and data reorganization by a cluster technique[J].Operations Research,1972,20(5):993-1009.
  • 3MICHALEWICZ Z.Genetic algorithm + data structure =evolution programs[M].3rd ed.Berlin:Springer-Verlag,1996.
  • 4WALTERS G A,SMITH D K.Evolutionary design algorithm for optimal layout of tree networks[J].Engineering Optimization,1995,24(4):261-281.
  • 5CUI M Y,SHANGGUAN Y L.Research on float-coded genetic algorithm based on wavelet denoising mutation[C]// Proceedings of the 3rd International Conference on Natural Computation.Piscataway:IEEE,2007:804-809.
  • 6CUI M Y.An improved float-coded genetic algorithm based on wavelet denoising mutation[C]// Proceedings of the 7th World Congress on Intelligent Control and Automation.Piscataway:IEEE,2008:4018-4023.
  • 7CUI M Y.FPRGA based on construction of multiwavelets in term of a novel transformation[C]// Proceedings of the 5th International Conference on Natural Computation.Piscataway:IEEE,2009:244-248.
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  • 9MARIANI V X,LUVIZOTTO G J,GUERRA F A.A hybrid shuffled complex evolution approach based on differential evolution for unconstrained optimization[J].Applied Mathematics and Computation,2011,217 (15):5822-5829.
  • 10YOON Y,KIM Y-H,MORAGLIO S,et al.A theoretical and empirical study on unbiased boundary-extended crossover for realvalued representation[J].Information Sciences,2012,183 (1):48-65.

共引文献4

同被引文献15

  • 1周明,孙树栋.遗传算法原理及应用[M].北京:国防工业出版社,2001.
  • 2Michalewicz Z.Genetic algorithms and optimal control problem[C]//Proc of 29th IEEE Conf on Decision and Control,1990:1664-1666.
  • 3Jomikow C Z,Michalewicz Z.An experimental comparison of binary and floating point representations in genetic algorithm[C]//Proc of 4th Conf on Genetic Algorithms.[S.l.]:Morgan Kaufmann,1991:31-36.
  • 4Eshelman L,Schaffer J.Real-coded genetic algorithms and interval schemata[M]//Whitley L.Foundations of genetic algorithms.San Francisco:Morgan Kaufmann Publishers,1993:187-202.
  • 5Walters G A,Smith D K.Evolutionary design algorithm for optimal layout of tree networks[J].Engineering Optimization,1995,24:261-281.
  • 6Cui Mingyi,Zhang Xinxiang,Mi Huichao.Research on threshold denoising of FPRGA[C]//Proceedings of the 8th International Conference on Software Engineering,Artificial Intelligence,Networking,and Parallel/Distributed Computing(SNPD 2007).IEEE,2007,1:1-8.
  • 7Mariani V C,Luvizotto Luiz L G J,Luvizotto G J,et al.A hybrid shuffled complex evolution approach based on differential evolution for unconstrained optimization[J].Applied Mathematics and Computation,2011,217:5822-5829.
  • 8Yoon Y,Kim Y H,Moraglio A,et al.A theoretical and empirical study on unbiased boundary-extended crossover for real-valued representation[J].Information Sciences,2012,183:48-65.
  • 9Chang Dongxia,Zhao Yao,Zheng Changwen.A genetic clustering algorithm using a message-based similarity measure[J].Expert Systems with Applications,2012,39:2194-2202.
  • 10Tang P H,Tseng M H.Adaptive directed mutation for realcoded genetic algorithms[J].Applied Soft Computing,2013,13:600-614.

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计算机工程与应用
2015年 第15期

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