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粒子群优化算法与BP算法和遗传算法的比较研究
Research of particle swarm optimization algorithm comparison with back-propagation algorithm and genetic algorithm
【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。
【Abstract】 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.
【关键词】 人工神经网络;
BP算法;
遗传算法;
粒子群优化算法;
【Key words】 artificial neural networks; back-propagation algorithm; genetic algorithm; partical swarm optimization algorithm;
【Key words】 artificial neural networks; back-propagation algorithm; genetic algorithm; partical swarm optimization algorithm;
【基金】 河南省教育厅软件科学项目(2003790350)
- 【文献出处】 信息化纵横 ,Informationization , 编辑部邮箱 ,2009年13期
- 【分类号】TP301.6
- 【被引频次】21
- 【下载频次】865