The prediction of port freight volume is of great significance to transportation and port planning. Based on the characteristics of grey GM (1,1) model and RBF neural network model, a combined forecasting model based on grey GM (1,1) model and RBF neural network model is constructed, and the port freight volume is predicted by field survey data. Experiments show that grey RBF neural network can improve the forecasting accuracy, which is effective and feasible for freight volume forecasting.


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    Title :

    Forecast of port freight volume based on grey RBF neural network combination model


    Contributors:
    Jiao, Yang (author) / Li, Lianbo (author) / Zhu, Zhenyu (author) / Wu, Wenhao (author)

    Conference:

    Sixth International Conference on Electromechanical Control Technology and Transportation (ICECTT 2021) ; 2021 ; Chongqing,China


    Published in:

    Proc. SPIE ; 12081


    Publication date :

    2022-02-07





    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English





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