## 基于MATLAB的粒子群优化算法研究

Research on particle swarm optimization algorithm based on MATLAB
Abstract:     Swarm intelligence is a new research field in recent years.It reveals the phenomenon of life and the evolution of life in different levels through the simulation of the phenomenon of life in nature.The particle swarm optimization algorithm is a kind of simulation of the birds' behavior.The PSO algorithm is similar to the genetic algorithm, and is a kind of iterative optimization tool.In this paper, the population size, inertia weight, learning factor and iteration number are studied in this paper,The results are compared with the results of different particle size and the number of iterations.
Keywords:    Swarm intelligence; Particle swarm optimization algorithm; Optimization tool; Group size; iterations

Abstract    i

1 绪论    3
1.1 群体智能    3
1.1.1 五条基本原则    3
1.1.2 特点    3
1.2 典型模型    3

2 粒子群优化算法    5
2.1 概述    5
2.2 几种粒子群算法    6
2.3 实验结果    13
2.3.1 基本粒子群算法（PSO）    13
2.3.2 带压缩因子的粒子群优化算法（YSPSO）    13
2.3.3 线性递减权重法（LinWPSO）    14
2.3.4 自适应权重法（SAPSO）    14
2.3.5 同步变化的学习因子粒子群算法（LnCPSO）    14
2.3.6 异步学习因子粒子群算法（AsyLnCPSO）    15
2.3.7 二阶振荡粒子群算法（SecVibratPSO）    15
3 对几种粒子群算法的对比    17
3.1 对比试验    17
3.2 实验步骤    17
3.3 试验结果    18
4 结论    19

1    绪论

1.1    群体智能

1.1.1    五条基本原则
(1) 邻近原则( Proximity Principle) ,群体能进行简单的空间和时间计算;
(2) 品质原则(Quality Principle) ,群体能够响应环境中的品质因子; 基于MATLAB的粒子群优化算法研究:http://www.lwfree.cn/jisuanjilunwen/20190924/39759.html
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