Railway freight transport plays an important role in transport, the accurate forecast of the freight volume is expected to guild the planning of railway business. The previous works on forecasting the freight volume have commonly used regression model, times series model, as well as grey model, however the useful information has been overlooked by using those prediction methods. The present study set out to forecast the railway freight volume by establishing an autoregressive integrated moving average model (ARIMA model), using the original data of railway freight volume in the Ningxia Hui Autonomous Region to do an empirical analysis. The results shown that the ARIMA model in forecasting railway freight volume can improve the prediction accuracy and could provide support for railway freight volume forecasting.


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    Titel :

    Research on Railway Freight Volume Prediction Based on ARIMA Model


    Beteiligte:
    Zhao, Jianyou (Autor:in) / Cai, Jing (Autor:in) / Zheng, Wenjie (Autor:in)

    Kongress:

    18th COTA International Conference of Transportation Professionals ; 2018 ; Beijing, China


    Erschienen in:

    CICTP 2018 ; 428-437


    Erscheinungsdatum :

    2018-07-02




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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