WNN-Based Prediction of Security Situation Awareness for the Civil Aviation Network

Abstract

The security of the civil aviation network is closely related to flight safety. Security situation prediction is the advanced stage of situational awareness in the civil aviation network. In this article, a prediction approach of security situations for the air traffic management network is proposed on the basis of the wavelet neural network. The proposed approach adopts the wavelet theory and neural network, combining a time-series forecasting method for the prediction of security situations in the civil aviation network. The experimental results show that this approach has the advantages of fast training and high prediction accuracy.