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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