A Stochastic Perturbing Particle Swarm Optimization Model
文献类型：会议论文
| 作者 | Lei Zhang; Ke Xu; Ruiqing Fu; Yongsheng Ou; Xinyu Wu |
| 出版日期 | 2010 |
| 会议名称 | 2010 2nd WRI Global Congress on Intelligent Systems, GCIS 2010 |
| 英文摘要 | The particle swarm optimization (PSO) algorithm is a generally used optimal algorithm, which exhibits good performance on optimization problems in complex search spaces. However, traditional PSO model suffers from a local minima, and lacks of effective mechanism to escape from it. This is harmful to its overall performance. This paper presents an improved PSO model called the stochastic perturbing PSO (SPPSO), which tries to overcome such premature convergence through perturbing the swarm with the perturbation and acceptance probability. The performance of the SPPSO is compared with the basic PSO (bPSO) on a set of benchmark functions. Experimental results show that, the new model not only effectively prevent the premature convergence, but also keep the rapid convergence rate like the bPSO. |
| 收录类别 | EI |
| 语种 | 英语 |
| 源URL | [http://ir.siat.ac.cn:8080/handle/172644/2890]  |
| 专题 | 深圳先进技术研究院_集成所 |
| 作者单位 | 2010 |
| 推荐引用方式 GB/T 7714 | Lei Zhang,Ke Xu,Ruiqing Fu,et al. A Stochastic Perturbing Particle Swarm Optimization Model[C]. 见:2010 2nd WRI Global Congress on Intelligent Systems, GCIS 2010. |
入库方式： OAI收割
来源：深圳先进技术研究院
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