计算机应用与软件Issue(4)：106-110,5.DOI:10.3969/j.issn.1000-386x.2014.04.027
一种GA-PSO算法优化BP网络的网络流量预测
A NETWORK TRAFFIC PREDICTION BASED ON BP NEURAL NETWORK OPTIMISED BY A GA-PSO ALGORITHM
摘要
Abstract
To analyse and study network traffic prediction has significance for information security and resource management of network.In order to more effectively and accurately predict network traffic,we propose a network traffic prediction model,which uses GA-PSO (genetic algorithm-particle swarm optimisation)to optimise BP neural network.First,we use BP neural network to build network traffic prediction model.Then we apply GA-PSO to optimise initial weights and thresholds of BP neural network.Finally,we use historical records of network traffic to simulate in experiments.Experimental results show that the BP neural network model optimised by GA-PSO speeds up the conver-gence rate and improves the prediction accuracy of network traffic.关键词
BP神经网络/遗传算法/粒子群优化算法/GA-PSO算法/网络流量/预测Key words
BP neural network/Genetic algorithm/Particle swarm optimisation/GA-PSO/Network traffic/Prediction分类
信息技术与安全科学引用本文复制引用
高玉明,张仁津..一种GA-PSO算法优化BP网络的网络流量预测[J].计算机应用与软件,2014,(4):106-110,5.基金项目
国家自然科学基金项目（41161065）；贵州省省长基金项目（黔省专合字（2009）115）；贵州省科技创新人才团队项目（黔科合人才团队（2012）4009）。 （）
