Identification of Key Nodes in Urban Subway Disaster Network Based on EDK Algorithm

Abstract

In order to systematically study the occurrence and propagation mechanism of disaster events in urban rail transit systems, based on complex network theory, a new coupling algorithm based on degree center algorithm and K-shell decomposition method—EDK algorithm is proposed. The algorithm combines the global and local attributes of the node, and uses the entropy method to determine the weight of the contribution of the index and the KS index to the importance of the node to obtain the comprehensive importance of the node. By comparing with existing node recognition algorithms, the verification algorithm has low complexity and high accuracy. Based on the domestic urban rail transit disaster event data for the past 20 years, construct a disaster-oriented network model, use the EDK algorithm to analyze the urban rail transit disaster risk system, identify key disaster nodes, combine actual data and compare the spread influence with the SI model to verify Disaster models and algorithms. The results show that the EDK algorithm can effectively identify the key disaster nodes in the urban rail transit disaster network, and the evaluation of the importance of the disaster nodes in the network is consistent with the actual situation.