| 基于个体决策机制的粒子群算法及应用 |
| |
| 引用本文： | 焦国辉,曾建潮. 基于个体决策机制的粒子群算法及应用[J]. 科技信息, 2013, 0(13): 32-33 |
| |
| 作者姓名： | 焦国辉 曾建潮 |
| |
| 作者单位： | [1]太原师范学院计算机中心,山西太原030012 [2]太原科技大学计算机学院,山西太原030024 |
| |
| 基金项目： | 国家自然科学基金项目,项目编号为60975074; 国家青年科学基金项目研究成果,项目编号为61003053 |
| |
| 摘 要： | 作为一种智能优化算法,粒子群算法中的粒子有不同的生活经验,因此每个粒子会做出不同的个体决策,但是这种决策机制在粒子群算法中并没有体现出来,因此本文通过引入个体决策机制的理论和方法通过个体历史适应值信息来改进粒子群算法。改进的粒子群算法应用到非线性方程组求解问题中,仿真结果表明它具有较大的优势。
|
| 关 键 词： | 粒子群算法 个体决策 历史适应值 非线性方程组 |
Application of Particle Swarm Optimization with Individual Decision Mechanism |
| |
| JIAO Guo-hui,ZENG Jian-chao. Application of Particle Swarm Optimization with Individual Decision Mechanism[J]. Science, 2013, 0(13): 32-33 |
| |
| Authors: | JIAO Guo-hui ZENG Jian-chao |
| |
| Affiliation: | 2 (1.Computer center of Taiyuan Normal University,Taiyuan Shanxi 030012,China; 2.Computer college of Taiyuan University of Science and Technology, Taiyuan Shanxi 030024,China) |
| |
| Abstract: | As an intelligence optimization algorithm,Since each particle maintains different living experience, Thus different individual will make a different decision, However this decision mechanism cannot reflect in Particle swam optimization（PSO）,herefore with the assistant of mature individual decision way and mechanism, this paper improved PSO with individual history fitness value. The improved PSO is applied into solving nonlinear equations problem, simulation results show more superior. |
| |
| Keywords: | Particle swarm optimization Individual decision History fitness value Nonlinear equations |
| 本文献已被 维普 等数据库收录！ |
|
