Application of ARIMA-SVM model in network traffic prediction
一种新的基于ARIMA-SVM网络流量预测研究

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.