Network traffic modeling and prediction based on RBF neural network

With the rapid development,the network now has a large size and high complexity,and consequently the network management is becoming increasingly difficult,so traffic prediction play more and more important role in network management.With a large amount of real traffic data collected from the actual network,a nonlinear network traffic model based on Radial Basis Function(RBF) neural network theory was constructed to predict the network traffic.The structure design and leaning algorithm of RBF neural network is presented.The simulation results on real network traffic show that the proposed RBF_based prediction scheme is efficient,and has better precision and adaptability compared with the traditional linear model and BP neural network.