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    ARTICLE

    Classifications of Stations in Urban Rail Transit based on the Two-step Cluster

    Wei Li1, 2, 3, Min Zhou1, *, Hairong Dong1

    Intelligent Automation & Soft Computing, Vol.26, No.3, pp. 531-538, 2020, DOI:10.32604/iasc.2020.013930

    Abstract Different types of stations have different functional roles in the urban rail transit network. Firstly, based on the characteristics of the urban rail transit network structure, the time series features and passenger flow features of the station smart card data are extracted. Secondly, we use the principal component analysis method to select the suitable clustering variables. Finally, we propose a station classification model based on the two-step cluster method. The effectiveness of the proposed method is verified in the Beijing subway. The results show that the proposed model can successfully identify the types of urban More >

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