火力与指挥控制2012，Vol.37Issue(2)：144-146,150,4.
基于改进粒子群优化RBF神经网络的算法
Algorithm Research of RBF Neural Network Based on Improved PSO
摘要
Abstract
In view of the defect of particle swarm optimization which easily gets into partial extremum, an improved particle swarm optimization algorithm is put out,and the algorithm is applied to the parameter selecting of RBF neural network kernel function. The best parameter vector is searched in the whole space, according to coding means, iterative formula, fitness function which are mentionedin the paper. The proves that RBF neural network based on improved PSO has faster convergent speed, and higher error precision.关键词
粒子群算法/RBF神经网络/局部搜索算子/仿真Key words
particle swarm optimization,RBF neural network,Local searching operator,simulation分类
信息技术与安全科学引用本文复制引用
李辉,蔡敏,谈亮..基于改进粒子群优化RBF神经网络的算法[J].火力与指挥控制,2012,37(2):144-146,150,4.基金项目
海军"十一五"预研基金资助项目(4010311030202) （4010311030202）
