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Rail Passenger Flow Prediction Combining Social Media Data for Rail Passenger

In: Liss 2021

Author

Listed:
  • Jiren Shen

    (Beijing Capital Agribusiness and Food Group)

Abstract

Comprehensive characterization and scientific prediction of urban rail transit passenger flow plays a very important role in the process of urban rail transit planning, construction and management operation. This study combines social media data to characterize urban rail transit passenger flow under the influence of different social events, and achieves a comprehensive characterization of rail transit passenger flow and scientific prediction of passenger flow.

Suggested Citation

  • Jiren Shen, 2022. "Rail Passenger Flow Prediction Combining Social Media Data for Rail Passenger," Lecture Notes in Operations Research, in: Xianliang Shi & Gábor Bohács & Yixuan Ma & Daqing Gong & Xiaopu Shang (ed.), Liss 2021, pages 672-681, Springer.
    • Handle: RePEc:spr:lnopch:978-981-16-8656-6_59
    DOI: 10.1007/978-981-16-8656-6_59
    as

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