The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence

doi:10.3969/j.issn.0372-2112.2012.07.013

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The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence

更新时间：2025-07-08

- The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence
- Acta Electronica Sinica Vol. 40, Issue 7, Pages: 1364-1367(2012)
- 作者机构：
  
  1. 闽江学院数学系,福建,福州,350108
  2. 闽江学院数学系,福建,福州,350108
- 作者简介：
- 基金信息：
- DOI：10.3969/j.issn.0372-2112.2012.07.013
  CLC： TP18
- Published：2012
- 稿件说明：
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The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence[J]. Acta Electronica Sinica, 2012, 40(7): 1364-1367.
DOI：

The Analysis of Continuous Particle Swarm Optimization Algorithm's Mean Square Convergence[J]. Acta Electronica Sinica, 2012, 40(7): 1364-1367. DOI： 10.3969/j.issn.0372-2112.2012.07.013.

摘要

粒子群优化算法是基于生物群体内个体间的合作与竞争等复杂行为产生的群体智能优化算法

已有的理论分析多在确定性的情况下进行算法收敛性分析.本文基于随机系统的矩方程法分析了连续型粒子群优化算法的均方收敛性

并给出了能够保证算法均方收敛域

最后通过仿真实验分析验证了相关结论.

Abstract

Particle swarm optimization (PSO) algorithm is a population-based

self-adaptive search optimization method motivated by the observation of simplified animal social behaviors.Most of the analysis of PSO algorithm is in the deterministic assumptions.Based on the theory of stochastic process

this paper studies the mean square convergence of the particle swarm optimization algorithm.Simulations demonstrate the validity of the proposed method.

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