Hyper passenger volume leads to crowdedness, trampling and falling to rail in subway station, optimum passenger organization will lessen emergency. The short-term passenger flow prediction is the basis of optimum passenger organization. To improve the prediction accuracy of passenger flow arriving at subway station, a PSO_LSTM network is built in the paper. First, the Automatic Fare Collection (AFC) transaction data of Shanghai Metro are processed and analyzed. Second, based on the particle swarm optimization (PSO), passenger prediction model is constructed. Third, to verify the model, the historical passenger flow data of Shanghai Railway Station of Shanghai Metro Line 1 are used to predict passenger arriving at the station in a certain time. The results show that mean absolute percentage error (MAPE) of passenger arriving prediction in test set with the PSO_LSTM network reduced by 3.15% and 3.59% respectively compared with that of original LSTM network and GRU network.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Short-term Passenger Flow Prediction of Subway Station Based on PSO_LSTM


    Additional title:

    Lect. Notes Electrical Eng.


    Contributors:
    Liang, Jianying (editor) / Jia, Limin (editor) / Qin, Yong (editor) / Liu, Zhigang (editor) / Diao, Lijun (editor) / An, Min (editor) / Song, Zhenyang (author) / Xu, Jie (author) / Li, Boyu (author) / Li, Xin (author)

    Conference:

    International Conference on Electrical and Information Technologies for Rail Transportation ; 2021 October 21, 2021 - October 23, 2021



    Publication date :

    2022-02-19


    Size :

    9 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English




    Short-term Passenger Flow Prediction of Subway Station Based on PSO_LSTM

    Song, Zhenyang / Xu, Jie / Li, Boyu et al. | British Library Conference Proceedings | 2022


    Short-term subway station entering passenger flow volume prediction method

    LYU LINGLING / HU DELAI / CHANG RUI et al. | European Patent Office | 2023

    Free access

    Subway line network passenger flow prediction method

    SHI YUE / ZHAO GENDANG / SHAN HUAJUN et al. | European Patent Office | 2023

    Free access

    Passenger subway at Padua Central station

    Ferrarese, L. | Engineering Index Backfile | 1932