On network security situation prediction based on RBF neural network
Yang Jiang, Chenghai Li, Lishan Yu, Bo Bao · 2017
Aiming at the problem of network security situation prediction, this paper studies the prediction method based on RBF neural network. Through training the RBF neural network, find out the nonlinear mapping relationship between the front N data and the subsequent M data, and then adjust the value of N to explore the different prediction results. The simulation result shows that the proposed method can accurately predict the results of the situation. Compared with the prediction based on BP neural network, the proposed method has a more accurate prediction and a faster convergence speed, a better prediction effect achieved.