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Issue title: Cross-domain Applications of Fuzzy Logic and Machine Learning
Guest editors: Ekaterina Isaeva and Álvaro Rocha
Article type: Research Article
Authors: Yu, Kanhua; * | Wang, Yalun | Zhao, Wei
Affiliations: School of Architecture, Chang’an University, Xi’an, China
Correspondence: [*] Corresponding author. Kanhua Yu, E-mail: [email protected].
Abstract: With the rapid development of rail transit, it puts forward higher requirements for safety. Once a safety accident occurs, it is highly destructive. It is of crucial significance and value to ensuring the safety of urban rail transit network by constructing an effective safety evaluation system. For purpose of this study, an urban transit network safety evaluation system based on topological genetic algorithm was constructed with an example of urban rail transit networking. Four indexes of urban rail transit safety were determined with the literature analysis method in combination with expert scoring method, including network heterogeneity, travel efficiency vulnerability, connection reliability and network capacity vulnerability. Besides, on the basis of some freeway networks and some freeway collecting toll data of Xi’an city, and the result of road network vulnerability, an index weight computing framework based on topological genetic algorithm was constructed. The result of simulation test shows that freeway manager should strengthen protection over nodes of large probability betweenness, and the urban transit network safety evaluation system based on topological genetic algorithm is of high feasibility and rationality.
Keywords: Topology, genetic algorithm, urban traffic, safety evaluation
DOI: 10.3233/JIFS-179760
Journal: Journal of Intelligent & Fuzzy Systems, vol. 38, no. 6, pp. 6825-6832, 2020
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