基于粒子群优化的反潜搜索研究

在分析目前反潜搜索现状的前提下,提出了使用粒子群优化算法进行反潜搜索,并针对基本粒子群优化算法存在早熟和后期收敛速度慢的局限性,对个体极值实行高斯变异,并使惯性因子随进化代数自适应调节,提高了全局搜索能力和后期收敛速度,改进了粒子群优化算法的潜艇搜索策略.经过实验验证,本算法可以有效地提高反潜搜索效率.

Antisubmarine Search Research on the Optimization of Particle Swarm

This paper analyzes status of antisubmarine search, brings forward search algorithm with particle swarm optimization. In order to deal with the problem of premature convergence and slow in the later phase of convergence by adding the Gauss mutation operator to the algorithm and self modifying inertia gene according to generation,this algorithm improves the ability of particle swarm optimization algorithm to break away from the local optimum solutions and searching speed in the later convergence phase. Through the experiment we found that the algorithm can improve ability of antisubmarine search efficiently.