Study of network traffic prediction

network traffic has a sudden

periodic

nonlinear characteristics

the traditional network traffic prediction model unable to establish accurate prediction model

lead to the prediction error

low accuracy of prediction. In order to improve the prediction accuracy of network traffic

put forward a kind of wavelet decomposition and support vector machine network traffic prediction model. Wavelet transform is adopted to network decomposition

the network traffic characteristics of components separated

then by using support vector machine to each component are predicted

the wavelet transform is adopted to predict the results of reconstruction of the components

network traffic has been the final forecasting result. The simulation results show that

compared with other prediction models

improve the prediction accuracy of network traffic

for the prediction of network traffic flow optimization provides reliable basis.