| 基于正态云的粒子群优化算法及其应用 |
| |
| 引用本文： | 刘衍民,赵庆祯,邵增珍. 基于正态云的粒子群优化算法及其应用[J]. 计算机工程, 2011, 37(17): 161-162,166 |
| |
| 作者姓名： | 刘衍民 赵庆祯 邵增珍 |
| |
| 作者单位： | 1. 遵义师范学院数学系,贵州遵义563002;山东师范大学管理与经济学院,济南250014
2. 山东师范大学管理与经济学院,济南,250014 |
| |
| 基金项目： | 山东省科技攻关计划基金资助项目(2009GG10001008) |
| |
| 摘 要： | 为辨识非线性系统Hammerstein模型，将非线性系统的辨识问题转化为参数空间上的优化问题，提出一种基于正态云模型的改进粒子群算法(NCPSO)。该算法采用动态变异概率，对全局最优粒子和粒子自身最优位置进行正态云变异，以产生新的粒子引导种群的飞行，有效避免早熟收敛。采用一种广义学习策略，提升粒子向最优解飞行的概率，将NCPSO算法用于对Hammerstein模型的辨识，相比其他算法，该算法辨识精度较高。
|
| 关 键 词： | 粒子群优化算法 正态云模型 系统辨识 动态变异 Hammerstein模型 |
| 收稿时间： | 2011-02-22 |
Particle Swarm Optimization Algorithm Based on Normal Cloud and Its Application |
| |
| LIU Yan-min,ZHAO Qing-zhen,SHAO Zeng-zhen. Particle Swarm Optimization Algorithm Based on Normal Cloud and Its Application[J]. Computer Engineering, 2011, 37(17): 161-162,166 |
| |
| Authors: | LIU Yan-min ZHAO Qing-zhen SHAO Zeng-zhen |
| |
| Affiliation: | LIU Yan-min1,2,ZHAO Qing-zhen2,SHAO Zeng-zhen2(1.Department of Math,Zunyi Normal College,Zunyi 563002,China,2.School of Management and Economics,Shandong Normal University,Jinan 250014,China) |
| |
| Abstract: | In order to identify the nonlinear system Hammerstein model,the problem of nonlinear system identification is changed into an optimization problem in parameter space.An improved Particle Swarm Optimization based on Normal Cloud(NCPSO) is proposed,in which a dynamic mutation is adopted to make the normal cloud mutation for the best performing particle(Gbest) in the swarm and the best previous position of each particle(Pbest).This mutation will generate the new Pbest and Gbest to lead the whole swarm flight,w... |
| |
| Keywords: | Particle Swarm Optimization(PSO) algorithm normal cloud model system identification dynamic mutation Hammerstein model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
| 点击此处可从《计算机工程》浏览原始摘要信息 |
|
点击此处可从《计算机工程》下载免费的PDF全文 |
