关键词: 改进的Elman神经网络, 网络流量, 建模, 自适应边界值, 季节周期性

Abstract: Aiming at the shortcomings of static feed forward network and Elman network in network traffic prediction，new modified Elman neural network is proposed，and a learning algorithm based on seasonal periodicity is proposed.With a large amount of network traffic data from the actual network，on basic of which，the network traffic is predicted.Simulation experimental results show this model has better effect of prediction.Compared with traditional linear model，BP neural network model and Elman neural network model，it has higher precision and better adaptability.The result shows the model is feasible，reasonable and effective.

Key words: modified Elman neural network, network traffic, modeling, adaptive boundary value, seasonal periodicity