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| Clonal Selection Algorithm with GEP Code for Function Modeling |
| MO Hai-Fang1,LI Kang-Shun2 |
1.Computer and Experiment Center,South-Central University for Nationalities,Wuhan 430074
2.School of Information,South China Agricultural University,Guangzhou 510642 |
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Abstract The clonal selection algorithm evolves through selecting best individuals,cloning the selected ones and hypermutation. The general method to find the best individuals is to sort the individuals according to their fitness. However,the GEP codes of those chromosomes with same fitness may be different. If duplicate individuals are allowed to appear in the sorted population,the duplicate superior individuals will be cloned excessively. In this case,the diversity of the population is decreased. If individuals are sorted just according to their fitness,the duplicate ones will be removed. And some best individuals with different codes may be abandoned. In order to maintain the diversity of population and increase the convergence rate,an improved clonal selection algorithm is proposed. Firstly,the individuals are sorted according to their fitness. Then,if there are multiple best individuals with same fitness,their codes are compared. The best individuals with different codes will be selected to clone. The experimental result shows that the proposed method maintains the diversity of population and increases the convergence rate.
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Received: 28 November 2012
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[1] Ferreira C. Gene Expression Programming: Mathematical Modeling by an Artificial Intelligence. 2nd Edition. Berlin,Germany: Springer-Verlag,2006
[2] Jiang Yue,Tang Changjie,Zheng Mingxiu,et al. Out-Breeding Strategy with Dynamic Fitness in Gene Expression Programming. Journal of Sichuan University: Engineering Science Edition,2007,39(2): 121-126 (in Chinese)
(姜 玥,唐常杰,郑明秀,等.基因表达式编程中动态适应的远缘繁殖策略.四川大学学报:工程科学版,2007,39(2):121-126)
[3] Li Kangshun,Pan Weifeng,Zhang Wensheng,et al. Automatic Modeling of Novel Gene Expression Programming Based on Statistical Analysis and Critical Velocity. Application Research of Computers,2008,25(8): 2312-2315 (in Chinese)
(李康顺,潘伟丰,张文生,等.基于统计分析和停滞速度的GEP自动建模.计算机应用研究,2008,25(8): 2312-2315)
[4] Wu Zhijian,Jiang Dazhi,Tang Mingduan. New Algorithm Based on Gene Expression Programming. Journal of System Simulation,2008,20(8): 1986-1989 (in Chinese)
(吴志健,姜大志,汤铭端.一种基于基因表达式程序设计的新算法.系统仿真学报,2008,20(8): 1986-1989)
[5] Hu Jianjun,Wu Xiaoyun. Superior Population Producing Strategy in Gene Expression Programming. Journal of Chinese Computer Systems,2009,30(8): 1660-1662 (in Chinese)
(胡建军,吴晓云.基因表达式编程中的优势种群产生策略.小型微型计算机系统,2009,30(8): 1660-1662)
[6] Xiang Jianping,Tang Changjie,Chen Yu,et al. CEA: Algorithm for Cluster-Elutriating Based on Minority Protection. Journal of Sichuan University: Engineering Science Edition,2009,41(5): 146-150 (in Chinese)
(向剑平,唐常杰,陈 瑜,等.CEA:基于弱势种群保护抗早熟的聚类淘汰算法.四川大学学报:工程科学版,2009,41(5): 146-150)
[7] Li Taiyong,Tang Changjie,Wu Jiang,et al. Adaptive Population Diversity Tuning Algorithm for Gene Expression Programming. Journal of University of Electronic Science and Technology of China,2010,39(2): 279-283 (in Chinese)
(李太勇,唐常杰,吴 江,等.基因表达式编程种群多样性自适应调控算法.电子科技大学学报,2010,39(2): 279-283)
[8] Xuan Shibin,Liu Yiguang. GEP Evolution Algorithm Based on Control of Mixed Diversity Degree. Pattern Recognition and Artificial Intelligence,2012,25(2): 186-194 (in Chinese)
(宣士斌,刘怡光.基于混合差异度控制的基因表达式编程.模式识别与人工智能,2012,25(2): 186-194)
[9] Litvinenko V I,Bidyuk P I,Bardachov J N,et al. Combining Clonal Selection Algorithm and Gene Expression Programming for Time Series Prediction // Proc of the IEEE Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications. Sofia,Bulgaria,2005: 133-138
[10] Karakasis V K,Stafylopatis A. Data Mining Based on Gene
Expression Programming and Clonal Selection // Proc of the IEEE Congress on Evolutionary Computation.Vancouver,Canada,2006: 514-521
[11] Gan Zhaohui,Yang Zhenkun,Li Gaobin,et al. Automatic Modeling of Complex Functions with Clonal Selection-Based Gene Expression Programming // Proc of the 3rd International Conference on Natural Computation.Haikou,China,2007: 228-232
[12] Gan Zhaohui,Tao Shang,Gang Shi,et al. Automatic Synthesis of Combinational Logic Circuit with Gene Expression Based Clonal Selection Algorithm // Proc of the 4th International Conference on Natural Computation. Jinan,China,2008: 278-282
[13] Tang Wan,Yang Ximin,Xie Xia,et al. Avidity-Model Based Clonal Selection Algorithm for Network Intrusion Detection // Proc of the 18th International Workshop on Quality of Service.Beijing,China,2010: 1-5
[14] de Castro L N,Von Zuben F J. Learning and Optimization Using the Clonal Selection Principle. IEEE Trans on Evolutionary Computation,2002,6(3): 239-251
[15] Lin Yishen,Peng Hong,Wei Jia. Function Finding in Niching Gene Expression Programming. Journal of Chinese Computer Systems,2008,29(11): 2111-2114 (in Chinese)
(林毅申,彭 宏,韦 佳.小生境基因表达式编程在函数发现的研究.小型微型计算机系统,2008,29(11): 2111-2114)
[16] Hu Jianjun,Tang Changjie,Peng Jing,et al. VPS-GEP: Skipping from Local Optimization Fast Algorithm. Journal of Sichuan University: Engineering Science Edition,2007,39(1): 128-133 (in Chinese)
(胡建军,唐常杰,彭 京,等.快速跳出局部最优的VPS-GEP算法.四川大学学报:工程科学版,2007,39(1): 128-133)
[17] Liu Qihong,Tang Changjie,Hu Jianjun,et al. Gene Expression Programming Based on Diversity-Guided Grading Evolution. Journal of Sichuan University: Engineering Science Edition,2006,38(6): 108-113 (in Chinese)
(刘齐宏,唐常杰,胡建军,等.多样性制导分段进化的基因表达式编程.四川大学学报:工程科学版,2006,38(6): 108-113)
[18] Dai Ming,Guo Chengwei,Tang Panshi. The Safe Ozone Pest Control in Greenhouse [EB/OL]. [2012-07-05]. http://wenku.baidu.com/view/af144268011ca300a6c39022.html (in Chinese)
(代 明,郭成维,唐磐石.温室中的绿色生态臭氧病虫害防治[EB/OL].[2012-07-05]. http: //wenku.baidu.com/view/
af144268011ca300a6c39022.html) |
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2013, Vol. 26 
