A Network Traffic Prediction Algorithm Based on Hybrid Model

摘要

Research network optimization control problem, network traffics have highly self-similarity, nonlinear and multi-scale features, the traditional forecasting methods based on linear data cannot accurately depict network traffic of nonlinear variation, and prediction accurate is low.In order to improve the network traffic prediction accurate, this paper proposed a network traffic hybrid prediction method based on wavelet analysis.The hybrid model uses wavelet analysis to decompose network traffic's the linear and nonlinear parts, and then used respectively ARIMA model and the BP neural network model to prediction its, lastly uses wavelet analysis to reconstruction the linear and nonlinear partial results and get mixed models eventually prediction result.Simulation results showed that the hybrid model is better than other network traffic prediction model;it has higher prediction accurate and is an effective analysis method for network optimization control