| 离散二进制粒子群算法分析 |
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| 引用本文： | 刘建华,杨荣华,孙水华.离散二进制粒子群算法分析[J].南京大学学报(自然科学版),2011(5):504-514. |
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| 作者姓名： | 刘建华 杨荣华 孙水华 |
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| 作者单位： | 福建工程学院计算机与信息科学系; |
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| 基金项目： | 福建省科技厅K类项目(JK2011035) |
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| 摘 要： | 粒子群算法（Particle Swarm Optimization,PSO）主要用优化计算实值的连续性问题,而离散二进制粒子群算法（Binary Particle Swarm Optimization,BPSO）则用来优化离散空间问题,它扩展了PSO算法的应用,现已广泛应用到各种离散优化问题计算中,但目前对BPSO算法...
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| 关 键 词： | 二进制粒子群算法 收敛性 位改变概率 模式定理 |
The analysis of binary particle swarm optimization |
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| Liu Jian-Hua,Yang Rong-Hua,Sun Shui-Hua.The analysis of binary particle swarm optimization[J].Journal of Nanjing University: Nat Sci Ed,2011(5):504-514. |
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| Authors: | Liu Jian-Hua Yang Rong-Hua Sun Shui-Hua |
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| Institution: | Liu Jian-Hua,Yang Rong-Hua,Sun Shui-Hua (Department of Computer and Information Science,Fujian University of Technology,Fuzhou,350108,China) |
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| Abstract: | Particle Swarm Optimization(PSO) is an evolutionary computation inspired by swarm intelligence.Compared to other evolutionary computation algorithms,PSO can not only solve a variety of difficult optimization problem,but also is ease to be used.So,PSO have been used across a wide range of applications.But PSO is mainly applied in the area of continuous space and rarely in that of discrete space.In order to be used in discrete space,binary Particle Swarm Optimization(BPSO) was developed to make PSO capable to... |
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| Keywords: | binary particle swarm optimization convergence schema theorem bit change probability expected value |
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