Airports Network Vulnerability Analysis based on Temporal Network

Airport operation performance has a significant impact on the operation of the air traffic network. Improving the recognition ability of important elements can help us ensure priority support objects and improve the performance of the overall performance. Generally, the traditional identification of important nodes in the network pays more attention to the topology structure and pays less attention to the space-time performance. Combined with the temporal network, this paper analyzes the importance of airport space-time in a day and analyzes the vulnerability of airport traffic evaluated by three indicators. Two-hop accessibility and Exceeded airport capacity load are designed to express the ability to serve passengers' travel and the pressure growth of the airport under abnormal conditions separately. The flight data is collected in July 2019 in China, and the experiment adopts the statistical simulation method concerning flight itineraries. The experimental results show that methods with a small time scale can greatly reduce the vulnerability of the airport network, indicating that it has a good ability to identify the spatio-temporal importance of elements. According to evaluations, the designed parameters can enrich the description of the air traffic network. The results provide useful reference values for the development of policies aimed at improving the resilience of air transport networks.