计算机工程与应用Issue(9)：65-68,115,5.DOI:10.3778/j.issn.1002-8331.1310-0168
CPSO算法优化神经网络重构的网络流量预测
Prediction research on network traffic of neural network reconstruc-tion based on CPSO algorithm optimization
摘要
Abstract
In order to improve the network traffic forecasting accuracy, this paper proposes a network traffic forecasting model based on phase space reconstruction and neural network optimized by CPSO algorithm(CPSO-BPNN). The param-eters of BP neural network, delay time and the embedding dimension are optimized by Chaos Particle Swarm Optimiza-tion algorithm, and the data of network traffic are reconstructed. BP neural network is used to train to establish network traffic forecasting model based on the optimal parameters, and the simulation experiments are carried out to test the perfor-mance of network traffic forecasting model. The simulation results show that the proposed model can describe the change trend of network traffic, and improve the network traffic forecasting accuracy.关键词
网络流量/预测精度/相空间重构/神经网络Key words
network traffic/forecasting accuracy/phase space reconstruction/neural network分类
信息技术与安全科学引用本文复制引用
尹向东,杨杰,屈长青..CPSO算法优化神经网络重构的网络流量预测[J].计算机工程与应用,2014,(9):65-68,115,5.基金项目
湖南省自然科学基金（No.11JJ6065）；湖南省教育厅科研项目（No.12C0681，No.10C0732）。 （）
