| 基于模式搜索法的云模型粒子群算法 |
| |
| 引用本文： | 吴建辉,王博华,张小刚,陈华.基于模式搜索法的云模型粒子群算法[J].控制与决策,2017,32(11):2076-2080. |
| |
| 作者姓名： | 吴建辉 王博华 张小刚 陈华 |
| |
| 作者单位： | 湖南大学信息科学与工程学院,长沙410082,湖南大学信息科学与工程学院,长沙410082,湖南大学电气与信息工程学院,长沙410082,湖南大学信息科学与工程学院,长沙410082 |
| |
| 基金项目： | 国家自然科学基金项目(61673162,61672216). |
| |
| 摘 要： | 针对粒子群算法在多峰寻优中易陷入局部最优、精度低、难以搜寻到较多的极值点等问题,提出一种基于模式搜索法的云模型粒子群算法.首先通过云模型粒子群算法在可行域内进行全局搜索,然后使用模式搜索法对搜索到的较优解进行局部寻优以提高解的精度.仿真测试表明,在保证收敛速度的同时,所提算法的收敛精度和搜索到的极值点数目均得到显著提高.
|
| 关 键 词： | 粒子群算法 模式搜索法 云模型 多峰函数 |
Cloud model particle swarm optimization algorithm based on pattern search method |
| |
| WU Jian-hui,WANG Bo-hu,ZHANG Xiao-gang and CHEN Hua.Cloud model particle swarm optimization algorithm based on pattern search method[J].Control and Decision,2017,32(11):2076-2080. |
| |
| Authors: | WU Jian-hui WANG Bo-hu ZHANG Xiao-gang and CHEN Hua |
| |
| Affiliation: | College of Information Science and Engineering,Hu''nan University,Changsha410082,China,College of Information Science and Engineering,Hu''nan University,Changsha410082,China,College of Electrical and Information Engineering,Hu''nan University,Changsha410082,China and College of Information Science and Engineering,Hu''nan University,Changsha410082,China |
| |
| Abstract: | In order to overcome the shortcomings of particle swarm optimization(PSO) in solving multimodal function optimization problems which includes easily falling into local minimum, low accuracy and difficultly searching extreme points as many as possible, a novel cloud model particle swarm optimization algorithm based on the pattern search method(PCPSO) is proposed. The cloud model particle swarm optimization(CPSO) algorithm is used to do global searching in the feasible zone, and then the pattern search method(PSM) is used to improve the accuracy of the sub-optimal solution. The simulation tests demonstrate that the proposed method can ensure the convergence speed, meanwhile the convergence accuracy and the number of extreme points are strikingly improved. |
| |
| Keywords: | |
|
| 点击此处可从《控制与决策》浏览原始摘要信息 |
|
点击此处可从《控制与决策》下载全文 |
|
