基于PSO-BP神经网络的网络流量预测与研究

传统网络流量预测采用线性方法进行处理,不能很好地满足要求.根据互联网通信量的自相似性,提出一种基于BP网络的粒子群优化PSO-BP算法进行网络流量预测,用PSO算法对BP网络节点的初始权值进行优化,并利用历史记录训练BP网络,采用Matlab进行仿真.试验结果表明,PSO-BP算法加快了BP网络收敛速度,训练结果的均方误差函数mse在5%以内,提高了网络流量预测精度.

PREDICTION AND RESEARCH ON NETWORK TRAFFIC BASED ON PSO-BP NEURAL NETWORK

Traditional prediction of network traffic is treated by linear method and cannot meet the demand well.According to self-similarity of the communication in internet,an algorithm of particle swarm optimized PSO-BP based on BP neural network is presented to predict the network traffic,PSO algorithm is applied to optimize the initial weights of nodes in BP neural network,historical records are used to train BP neural network,and Matlab is used in simulation.Experiment results show that the PSO-BP algorithm spee...