To identify the node importance of a passenger transport network in metropolitan areas, this study measures the synthetical passenger node importance of cities in three aspects by considering space of flow theory in a social network. First, a framework with eight selected basic features is constructed to identify basic urban attribute indexes by using the traditional node importance method in transport network design. Second, network topology attributes (i.e., aggregation and betweenness degrees) are proposed on the basis of a passenger transport network. Third, an urban linkage model based on the gravity model is developed by considering urban linkage in metropolitan areas. The three aspects are integratively evaluated by using the entire-array-polygon method, and then cluster analysis of the comprehensive node importance of a passenger network is performed using the k-means algorithm. A case study of the Chengdu metropolitan area in Sichuan is conducted, and results verify that the proposed algorithm is reasonable and suitable for identifying the node importance of a passenger transport network in a megalopolis.
Identification of the Node Importance of a Passenger Transport Network in Metropolitan Areas
2019-09-01
92019-01-01 pages
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