计算机应用研究2012，Vol.29Issue(11)：4293-4295,4299,4.DOI:10.3969/j.issn.1001-3695.2012.11.075
基于IPSO混沌支持向量机的网络流量预测研究
Study on network traffic prediction of C-SVM based on IPSO
摘要
Abstract
Aiming the limitation of the conventional parameter optimized algorithm in C-SVM, this paper proposed an IPSO algorithm. The algorithm extended the search time in the beginning and final phase of the iterative course, in order to achieve the balance between global and local search capabilities. Then it optimized the parameters of C-SVM, and built the prediction model of C-SVM based on IPSO. The results of application example show that the model is efficient in network traffic prediction with higher optimized efficiency, prediction accuracy and better stability.关键词
网络流量预测/混沌支持向量机/改进粒子群算法/遗传算法Key words
network traffic prediction/ chaos support vector machine (C-SVM)/ improved particle swarm optimization ( EP-SO ) algorithm/ genetic algorithm ( GA)分类
信息技术与安全科学引用本文复制引用
尹波,夏靖波,付凯,陈茂..基于IPSO混沌支持向量机的网络流量预测研究[J].计算机应用研究,2012,29(11):4293-4295,4299,4.基金项目
全军军事学研究生课题(2010XXXX-488) （2010XXXX-488）
陕西省自然科学基金资助项目(2009JM8001-1) （2009JM8001-1）
