A Combined Prediction Model of Internet Traffic Based on Neural Network
一种基于神经网络的网络流量组合预测模型

The Internet traffic is correlated and non-stationary time series.By analyzing some past traffic models,a new prediction model was established.In this model,Internet traffic was pretreated with wavelet method at first.Then,linear NN(Neural Network) and Elman NN were used respectively to make prediction.Therefore,the correlation and non-stationary characteristics of the traffic could be described.Finally,the two predictions were combined into the final result through BP neural network.Through one-step and multi-step prediction simulations on different kinds of traffic respectively,it is verified that the combined model can predict more precisely than the individual model.