With the large-scale construction of China's high-speed railway network, the demand for passenger flow is growing and varies in different seasons. Therefore, refinement operational requirements are increasingly prominent. However, the passenger flow itself has time-varying characteristics, and the division of passenger flow seasons and periods is divided by manual methods and experience subjectively. As a result, it is difficult to adjust it dynamically with the passenger flow changing dynamically. There are few studies on the seasons and periods of the division about high-speed railway passenger flow at home and abroad. In this study, the seasonal and period division methods of high-speed railway passenger flow were studied, the dynamic characteristics of passenger flow were analyzed, and the annual passenger flow fluctuation was considered. Then, the high-speed railway passenger flow was divided into seasons by using the firefly affinity propagation algorithm. Meanwhile, the high-speed railway passenger flow was divided into periods by employing the orderly clustering algorithm with the consideration of the daily passenger flow fluctuation.


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    Titel :

    Seasonal and Period Division Method for Dynamic Passenger Flow of High-Speed Railway


    Weitere Titelangaben:

    Smart Innovation, Systems and Technologies


    Beteiligte:
    Ni, Shaoquan (Herausgeber:in) / Wu, Tsu-Yang (Herausgeber:in) / Geng, Jingchun (Herausgeber:in) / Chu, Shu-Chuan (Herausgeber:in) / Tsihrintzis, George A. (Herausgeber:in) / Han, Hui (Autor:in) / Zou, Xinqian (Autor:in) / Gao, Yiyuan (Autor:in) / Guo, Xiuyun (Autor:in)


    Erscheinungsdatum :

    2023-05-15


    Format / Umfang :

    15 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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