This paper through studying the theory of data warehouse and data mining, applies these technologies to deal with the large number data in the Ticket Selling and Reserving System of Chinese Railway (TRS), uses the effective data mining to the passenger flow analysis, builds up the logical forecasting and analysis model. This paper firstly discusses the current situation and problems faced by forecasting of passenger flow, then applies the data warehouse technology to design the data mart of this subject. Next, samples and analyses this data which collecting in data mart adopting neural network method, builds data analysis model carrying out research and the experiment, finally puts forward a feasible forecast model for the passenger flow forecasting.


    Access

    Access via TIB

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Application of Data Mining in the Forecasting of Railway Passenger Flow


    Contributors:
    Zheng, Dan (author) / Wang, Yao (author) / Tang, Peng-Zhi (author) / Wu, Yan-Ping (author)


    Publication date :

    2013


    Size :

    4 Seiten




    Type of media :

    Conference paper


    Type of material :

    Print


    Language :

    English





    Railway passenger demand forecasting

    Smith, Tim / Faber, Oscar | IuD Bahn | 1998


    SARIMA MODELLING APPROACH FOR RAILWAY PASSENGER FLOW FORECASTING

    Miloš Milenković / Libor Švadlenka / Vlastimil Melichar et al. | DOAJ | 2018

    Free access

    Study of Railway Passenger Flow Forecasting Based on Season Index

    Huang, Ying ;Lu, Zheng Ye ;Ji, Shou Wen | Trans Tech Publications | 2014