[1]林金星,沈炯,肖国涛,等.一种基于分层模糊控制的免疫遗传优化算法[J].东南大学学报(自然科学版),2005,35(1):46-49.[doi:10.3969/j.issn.1001-0505.2005.01.010]
 Lin Jinxing,Shen Jiong,Xiao Guotao,et al.Immune genetic optimization algorithm based on multilayer fuzzy control[J].Journal of Southeast University (Natural Science Edition),2005,35(1):46-49.[doi:10.3969/j.issn.1001-0505.2005.01.010]
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一种基于分层模糊控制的免疫遗传优化算法()
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《东南大学学报(自然科学版)》[ISSN:1001-0505/CN:32-1178/N]

卷:
35
期数:
2005年第1期
页码:
46-49
栏目:
自动化
出版日期:
2005-01-20

文章信息/Info

Title:
Immune genetic optimization algorithm based on multilayer fuzzy control
作者:
林金星1 沈炯1 肖国涛2 李益国1 王培红1
1 东南大学动力工程系, 南京 210096; 2 南京西门子电站自动化有限公司, 南京 210003
Author(s):
Lin Jinxing1 Shen Jiong1 Xiao Guotao2 Li Yiguo1 Wang Peihong1
1 Department of Power Engineering, Southeast University, Nanjing 210096, China
2 Nanjing Siemens Power Plant Automation Ltd, Nanjing 210003, China
关键词:
免疫遗传算法 信息熵 种群多样性 模糊控制器
Keywords:
immune genetic algorithm information entropy population diversity fuzzy controller
分类号:
TP18
DOI:
10.3969/j.issn.1001-0505.2005.01.010
摘要:
针对标准遗传算法的不足,借鉴生物免疫机理和人脑模糊思维功能提出一种新的基于分层模糊控制的免疫遗传算法.该算法利用免疫系统独特性网络学说,改进标准遗传算法选择算子,提高了种群多样性; 同时从环境、种群、个体和基因角度,全面分析算法寻优性能和各种进化参数的启发式模糊关系,采用模糊推理动态调整交叉率、交叉位置和变异率,减小了标准遗传操作的随机性.实验结果表明,新算法不仅可有效克服标准遗传算法的缺陷,而且收敛速度、计算精度和算法稳定性也得到明显提高.
Abstract:
Aiming at the insufficiencies of standard genetic algorithm(SGA), a novel immune genetic algorithm based on multilayer fuzzy control(MFCMGA)is proposed, which adopts the biological immune theory and fuzzy thinking function of human. In order to increase the diversity of population, MFCMGA uses idiotypic immune network theory to improve the selection operator of SGA. Meanwhile in order to decrease the randomicity of SGA, the crossover probability, crossover position and mutation probability are adjusted dynamically by using fuzzy inference, which is based on analyzing the heuristic fuzzy relationship between algorithm performance and evolutionary parameters from the viewpoints of environment, population, individual and gene. Simulation results show that MFCMGA effectively overcomes the shortcomings of SGA, and evidently improves the convergent speed, computing precision and algorithm stability.

参考文献/References:

[1] 李敏强,寇纪凇,林丹,等.遗传算法的基本理论与应用[M].北京:科学出版社,2002.13-14.
[2] Francisco H,Manuel L.Adaptive genetic operators based on coevolution with fuzzy behaviors [J]. IEEE Trans on Evolutionary Computation,2001, 5(2):149-165.
[3] 何琳,王科俊,李国斌,等.遗传算法种群多样性的分析研究[J].哈尔滨工程大学学报,1999,20(4):27-33.
  He Lin,Wang Kejun,Li Guobin,et al.The analysis and research of genetic algorithms’ population diversity[J]. Journal of Harbin Engineering University,1999,20(4):27-33.(in Chinese)
[4] Srinivas M,Patnaik L M.Adaptive probabilities of crossover and mutations in gas [J].IEEE Trans on SMC, 1994,24(4):656-667.
[5] 马钧水,刘贵忠,贾玉兰.改进遗传算法搜索性能的大变异操作[J].控制理论与应用,1998,15(3):404-408.
  Ma Junshui,Liu Guizhong,Jia Yulan.The big mutation:an operation to improve the performance of genetic algorithms[J].Control Theory and Applications, 1998,15(3):404-408.(in Chinese)
[6] Liao Gwo-Ching,Tsao Ta-Peng.Application embedded chaos search immune genetic algorithm for short-term unit commitment[J].Electric Power Systems Research, 2004, 71:135-144.
[7] 郑日荣,毛宗源,罗欣贤.改进人工免疫算法的分析研究[J].计算机工程与应用,2003(34):35-37.
  Zheng Rirong,Mao Zongyuan,Luo Xinxian.A study on modified artificial immune algorithms [J]. Computer Engineering and Applications, 2003(34):35-37.(in Chinese)
[8] 赵振宇,徐用懋.模糊理论和神经网络的基础与应用 [M].北京:清华大学出版社,1996.27-31.
[9] Eiben Agoston Endre,Hinterding Robert,Michalewicz Zbigniew.Parameter control in evolutionary algorithms[J].IEEE Trans on Evolutionary Computation,1999,3(2):124-141.

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备注/Memo

备注/Memo:
基金项目: 教育部高等学校博士点基金资助项目(20020286001)、江苏省自然科学基金资助项目(BK2001005).
作者简介: 林金星(1978—),男,博士生; 沈炯(联系人),男,博士,教授,博士生导师,shenj@seu.edu.cn.
更新日期/Last Update: 2005-01-20