Research on Network Traffic Prediction Model Based on Neural Network

Network traffic prediction has become an important means for network security monitoring and security assessment. Through network traffic prediction, it can detect network failures effectively, optimize network performance and ensure network security. This paper proposes a network traffic prediction model based on neural network which combined deep recurrent neural network (RNN) and gated recurrent unit (GRU) neural network applied to the network traffic prediction. The analytical results are verified by numerical computation and simulations. It is shown that the network traffic prediction result of the model is close to the actual value of the network traffic in the real environment.