1373075 - Robustness analysis for China’s airport network based on multi-layer temporal complex network model.

Abstract: In order to meet passengers' demands for increasing travel efficiency, the structure of China's airport network will become more and more complex, and its operating environment has become more complex. So, it is important to measure the robustness of China's airport network under the influence of complex disturbance factors, this paper proposes an airport network robustness analysis method based on the multi-layer temporal complex network model (MTNM) by introducing the time attribute. Firstly, we establish the network structure characteristics such as temporal degree, temporal closeness centrality (TC) and temporal betweenness centrality (TB) of airport network nodes, and take temporal network efficiency and temporal maximum connected subgraph as indicators, then inflection points of loss fitting curves for temporal network characteristics metrics under random attacks and deliberate attack can be identified to evaluate network robustness. The results show that the attack ratio reaches 86% under random attacks, inflection point of loss fitting curves will appear, and relative loss of global temporal network efficiency will amount to 53.57%, while reduction rate of the maximum connected subgraph connected subgraph reaches 12.07%; when the attack percentage reaches 76.06% under deliberate attack, the inflection point of the loss curve appears, and relative loss of global temporal network efficiency will amount to 77.86%, while reduction rate of the maximum connected subgraph connected subgraph reaches 51.3%. For both attack strategies after the inflection point, the temporal network efficiency and temporal maximum connected subgraph reduction rate accelerates, and the network is in a paralyzed state.
Keywords: temporal networks; multilayer networks; airport networks; loss curve; robustness assessment