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.


    Access

    Check access

    Check availability in my library

    Order at Subito €


    Export, share and cite



    Title :

    Research on Railway Freight Volume Prediction Based on ARIMA Model


    Contributors:
    Zhao, Jianyou (author) / Cai, Jing (author) / Zheng, Wenjie (author)

    Conference:

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


    Published in:

    CICTP 2018 ; 428-437


    Publication date :

    2018-07-02




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English




    Freight traffic of civil aviation volume forecast based on hybrid ARIMA-LR model

    Chen, Bin / Liu, Jiacheng / Ruan, Zhouying et al. | British Library Conference Proceedings | 2022


    Freight traffic of civil aviation volume forecast based on hybrid ARIMA-LR model

    Chen, Bin / Liu, Jiacheng / Ruan, Zhouying et al. | SPIE | 2022



    Railway Freight Volume Prediction Based on Support Vector Regression (SVR)

    Liu, Yan ;Lang, Mao Xiang | Trans Tech Publications | 2014