%0 Journal Article
%T Application of ARIMA-SVM model in network traffic prediction<br>一种新的基于ARIMA-SVM网络流量预测研究
%A SHAO Xin
%A <br>邵忻
%J 计算机应用研究
%D 2012
%I 
%X Network flow is affected by many factors, its change is cyclical, nonlinear and stochastic characteristics. This paper used ARIMA model and SVM model to establish a network traffic prediction model. It used ARIMA forecasting network traffic cyclic and linear trend, and then used SVM to network flow nonlinear and stochastic trend fitting. At last two results again entered the SVM integration, network traffic had been the final prediction results. By using network flow data for model performance test, simulation results show that, ARIMA-SVM increases network traffic prediction accuracy, reduces the prediction error, and it can fully characterize network traffic variation.
%K ARIMA(autoregressive integrating moving average)
%K SVM(support vector machine)
%K network traffic
%K prediction<br>自回归滑动平均模型(ARIMA)
%K 支持向量机(SVM)
%K 网络流量
%K 预测
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=A9D9BE08CDC44144BE8B5685705D3AED&aid=F886A295C1E57CC5ABCF7CA94BEC2764&yid=99E9153A83D4CB11&vid=771469D9D58C34FF&iid=94C357A881DFC066&sid=8080149E52358D01&eid=BE1B94DF77D86B4A&journal_id=1001-3695&journal_name=计算机应用研究&referenced_num=0&reference_num=8