Abstract：The topological characteristics and resilience analysis of public transportation systems are of great significance in urban management to ensure its safe and sustainable operation. This paper constructs a bus-metro interdependent network model based on the passenger transfer relationship and uses deep learning to identify their network topology attributes. A comprehensive importance indicator of the nodes is established by entropy weight-technique for order preference by similarity to ideal solution (EWM-TOPSIS), and the resilience of the network under different recovery strategies are analyzed. In order to verify the applicability and accuracy of the method, this study takes Wuhan's public transportation network as an example, which has practical guiding significance for the post-disaster recovery and operation management of the urban public transportation system.
王淑良, 陈辰, 张建华, 栾声扬. 基于复杂网络的关联公共交通系统韧性分析[J]. 复杂系统与复杂性科学, 2022, 19(4): 47-54.
WANG Shuliang, CHEN Chen, ZHANG Jianhua, LUAN Shengyang. Resilience Analysis of Public Interdependent Transport System Based on Complex Network[J]. Complex Systems and Complexity Science, 2022, 19(4): 47-54.
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