Flight Delay Propagation Prediction Model Based on CBAM-CondenseNet

Abstract

For the problem of flight delay propagation caused by flight delay, a flight delay wave prediction model based on CBAM-CondenseNet is presented. Firstly, by analyzing the delays propagation in the aviation network caused by flight delays, the flight chain affected by the pre-order delays is determined; Secondly, the selected flight chain data is cleaned and the flight information and airport information are fused; Finally, an improved CBAM-CondenseNet algorithm is proposed to extract the number of fused flights. According to feature extraction, a Softmax classifier is constructed to predict the delays of the first departure flights and the subsequent flights. The CBAM-CondenseNet algorithm proposed in this paper combines the advantages of CondenseNet and CBAM, and uses channel and spatial attention mechanism to enhance the transmission of deep information in network structure. The experimental results show that the improved algorithm can effectively improve the network performance, and the prediction accuracy can reach 97.55%.