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一种新的基于不同疫情防控政策响应视角的机场网络系统弹性分析方法。

A novel resilience analysis methodology for airport networks system from the perspective of different epidemic prevention and control policy responses.

机构信息

College of Air Traffic Management, Civil Aviation Flight University of China, Guanghan, Sichuan, China.

National Key Laboratory of CNS/ATM, School of Electronic and Information Engineering, Beihang University, Beijing, China.

出版信息

PLoS One. 2023 Feb 27;18(2):e0281950. doi: 10.1371/journal.pone.0281950. eCollection 2023.

Abstract

As the COVID-19 pandemic fades, the aviation industry is entering a fast recovery period. To analyze airport networks' post-pandemic resilience during the recovery process, this paper proposes a Comprehensive Resilience Assessment (CRA) model approach using the airport networks of China, Europe, and the U.S.A as case studies. The impact of COVID-19 on the networks is analyzed after populating the models of these networks with real air traffic data. The results suggest that the pandemic has caused damage to all three networks, although the damages to the network structures of Europe and the U.S.A are more severe than the damage in China. The analysis suggests that China, as the airport network with less network performance change, has a more stable level of resilience. The analysis also shows that the different levels of stringency policy in prevention and control measures during the epidemic directly affected the recovery rate of the network. This paper provides new insights into the impact of the pandemic on airport network resilience.

摘要

随着 COVID-19 大流行的消退,航空业正进入快速复苏阶段。为了分析机场网络在复苏过程中的后疫情时代弹性,本文提出了一种综合弹性评估(CRA)模型方法,以中国、欧洲和美国的机场网络作为案例研究。在将这些网络的模型用实际的空中交通数据填充后,分析了 COVID-19 对网络的影响。结果表明,尽管欧洲和美国的网络结构受到的损害比中国更严重,但大流行确实对这三个网络造成了损害。分析表明,中国作为网络性能变化较小的机场网络,具有更稳定的弹性水平。分析还表明,疫情期间防控措施的不同严格程度直接影响了网络的恢复速度。本文为机场网络弹性受大流行影响提供了新的见解。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fc82/9970082/5c0e6bdeef87/pone.0281950.g001.jpg

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