Network Traffic Prediction Based on Neural Network Optimized by GA

In order to improve the network traffic prediction accuracy,this paper proposes a network traffic prediction method based on RBF neural network optimized by genetic algorithm which uses the relation between phase space reconstruction and parameters of prediction model.Firstly,phase space reconstruction and the parameters of RBF neural network are coded,and then the model prediction accuracy is used as the objection function,and optimal parameters of the model are selected by genetic algorithm,lastly,the simulation experiments are carried out to test model's performance.The results show that,compared with the traditional models,the proposed model improves the prediction accuracy.