摘要
讨论了粒子群优化算法的基本原理和实现步骤,分析了该算法中各参数的设置。通过一个测试函数,对粒子群优化算法与遗传算法和BP算法分别进行了比较,结果表明粒子群优化算法在找寻最优解效率上好于其他两种算法。
This paper discusses particle swarm Optimization algorithm principle and the step of implementation, and then analyzes the setting of each parameter. Particle swarm optimization algorithm is compared with genetic algorithm and back-propagation algorithm through the same mathematic function. The comparative result indicates that particle swarm optimization algorithm can more easily obtain the optimum solutions than genetic algorithm and back-propagation algorithm.
基金
河南省教育厅软件科学项目(2003790350)
关键词
人工神经网络
BP算法
遗传算法
粒子群优化算法
artificial neural networks
back-propagation algorithm
genetic algorithm
partical swarm optimization algorithm
