微型机与应用2012，Vol.31Issue(1)：64-66,72,4.
自适应变异粒子群算法优化BP神经网络在音乐分类中的应用
Music category based on adaptive mutation particle swarm optimization BP neural network
摘要
Abstract
Adaptive mutation particle swarm optimization algorithm has the advantages of PSO and GM algorithm. Using the algorithm to find a better network weights and threshold can not only overcome the slow convergence of basic and easy to fall into local minimum limitations,but also has a high accuracy of the model. The simulation results show that the algorithm has higher accuracy than traditional classification methods, and verified adaptive mutation particle swarm optimization is an effective classification to optimize BP neural network.关键词
音乐分类/神经网络/粒子群优化算法/交叉算子Key words
music category/neural network/particle swarm optimization（PSO）/hybrid genes分类
机械制造引用本文复制引用
彭建喜,喻晓..自适应变异粒子群算法优化BP神经网络在音乐分类中的应用[J].微型机与应用,2012,31(1):64-66,72,4.基金项目
国家自然科学基金 （）
