Research on subway passenger flow prediction based on bp neural network

Haibo Zhang; Yuqing Zhou; Xiaolin Fu; Xuenian Yang; Qizhi Yang

doi:10.1117/12.3054487

20 December 2024 Research on subway passenger flow prediction based on bp neural network

Haibo Zhang, Yuqing Zhou, Xiaolin Fu, Xuenian Yang, Qizhi Yang

Author Affiliations +

Proceedings Volume 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024); 134214Z (2024) https://doi.org/10.1117/12.3054487
Event: Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 2024, Dalian, China

Abstract

The swift progress of urban rail transit necessitates precise passenger flow forecasting, which serves as the cornerstone for rational train scheduling. It augments the efficiency of train formation capabilities and minimizes the time passengers spend reaching platforms and waiting for trains. This not only diminishes the operational expenses for the operating entity but also curtails travel time and economic costs for passengers. This article utilizes passenger flow data from Kuanzhai Alley Station on Chengdu Metro Line 4 as the research foundation. The gathered data is partitioned into training and validation sets, and a BP neural network-based time series passenger flow forecasting model is established using historical passenger flow data. By comparing the predicted results with actual outcomes, the experimental analysis reveals that the prediction method demonstrates high accuracy.

(2024) Published by SPIE. Downloading of the abstract is permitted for personal use only.

Citation Download Citation

Haibo Zhang, Yuqing Zhou, Xiaolin Fu, Xuenian Yang, and Qizhi Yang "Research on subway passenger flow prediction based on bp neural network", Proc. SPIE 13421, Eighth International Conference on Traffic Engineering and Transportation System (ICTETS 2024), 134214Z (20 December 2024); https://doi.org/10.1117/12.3054487

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