| 粒子群优化算法的改进及其实现 |
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| 引用本文： | 赵秋亮,吴秋波,唐志波. 粒子群优化算法的改进及其实现[J]. 现代电子技术, 2007, 30(14): 82-84 |
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| 作者姓名： | 赵秋亮 吴秋波 唐志波 |
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| 作者单位： | 1. 浙江海洋学院,浙江,舟山,316000
2. 成都理工大学,四川,成都,610059 |
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| 摘 要： | 基本粒子群优化算法存在着"早熟"现象。究其主要原因是由于全局最优粒子的运动形式滞留在局部最优。为此,根据基本PSO算法的特点,在粒子运动过程中加入了个体小概率随机变异,增强了粒子运动形式改变能力,减小了陷入局部最优的可能性。通过数值计算结果表明,该方法能有效地解决粒子群优化"早熟"问题。
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| 关 键 词： | 粒子群优化算法 随机变异 早熟 遗传算法 |
| 文章编号： | 1004-373X（2007）14-082-03 |
| 收稿时间： | 2007-03-15 |
| 修稿时间： | 2007-03-15 |
A Modified Particle Swarm Optimization and Its Realization |
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| ZHAO Qiuliang,WU Qiubo,TANG Zhibo. A Modified Particle Swarm Optimization and Its Realization[J]. Modern Electronic Technique, 2007, 30(14): 82-84 |
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| Authors: | ZHAO Qiuliang WU Qiubo TANG Zhibo |
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| Affiliation: | 1. Zhejiang Ocean University, Zhoushan, 316000. China; 2. Chengdu University of Technology, Chengdu. 610059, China |
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| Abstract: | Standard Particle Swarm Optimization(PSO) has premature phenomenon,and the reason is that the motion of the globe best particle plunges into local optimization.Thinking over this point,we add the small probability random mutation to strengthen the motion of the particles,reduce the chance of slumping local optimization.The result of numerical computation shows that the modified algorithm can resolve the premature problem of PSO efficiently. |
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| Keywords: | PSO random mutation premature genetic algorithm |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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