摘要
Abstract
In this paper ,the mutation operator ,which is used in Genetic Algorithm ,is introduced into the basical PSO algorithm .By mutation operator control function ,the training process of the PSO algorithm is divided into early phase and late phase .In the early phase of the algorithm train ,the mutation rate is larger ,so the more particles are chosen to take the mutation operation ,in order to enhance the diversity of the population’s particles ,and the PSO algorithm can hunt in a large solution space to avoid being trapped in the local optimal solution too early .In the late phase of the algorithm train ,the mu‐tation rate is smaller ,so the less particles are chosen to take the mutation operation ,in order to attenuate the diversity of the population’s particles ,therefore the PSO algorithm can hunt in a smaller solution space to improve the convergence accuracy of the algorithm .Simulation results show that ,the convergence precision of this algorithm is higher ,and solution of the local minimum problem is quite well .关键词
PSO 算法/遗传算法/变异算子/控制函数/局部极小值Key words
PSO algorithm/genetic algorithm/mutation operator/control function/local minimum分类
信息技术与安全科学
