A Prediction Method Based on Neural Network for Flight Turnaround Time at Airport

The present flight on-time performance is continuously deteriorating. During the flight turnaround at a given airport, the delay of former flight will affect its subsequence flight and even be propagated to other flights in the airport, which counts against the normal operation of airport. To effectively control the influence, prediction of flight turnaround time at the airport has become an urgent problem to be addressed. To predict a reasonable turnaround time for flights, which have insufficient turnaround time in the airport, this paper firstly analyzes the critical factors that affect the flight turnaround time quantitatively and qualitatively, and then establishes a flight turnaround time prediction model based on neural network. The established model is validated through the case study using real data set collected from Beijing Capital International Airport.