This essay aims to make a prediction of the GDP of Baoshan City in the following five years by employing the GM (1, 1) models which is established on the basis of Gray system theory. The prediction shows that gray equation dimension grey number successively supplement (EDGNSS) GM (1, 1) forecast model can be a very good simulation of the interflow of the goods and materials in the macroscopic logistics system, making its role of being a white information time data to the fullest and reducing the gray space between the prediction value. The gray parameters and the models will be revised as the prediction step forward a single step and finally the prediction value will come into being in this dynamic process. This model is of high precision and requires few statistics. It proves to be a very method for macroscopic logistic system.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Logistics Demand Forecast Based on Gray System Theory


    Beteiligte:
    Liang, X. C. (Autor:in) / Shuai, B. (Autor:in) / Yang, Z. Y. (Autor:in)

    Kongress:

    First International Conference on Transportation Engineering ; 2007 ; Southwest Jiaotong University, Chengdu, China



    Erscheinungsdatum :

    09.07.2007




    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Logistics Demand Forecast Based on Gray System Theory

    Liang, X.C. / Shuai, B. / Yang, Z.Y. et al. | British Library Conference Proceedings | 2007



    BP neural network based on Qingdao City air logistics demand forecast

    Chen, Wenbo / Cao, Yunchun | British Library Conference Proceedings | 2023



    DEMAND FORECAST GUIDANCE SYSTEM AND DEMAND FORECAST GUIDANCE PROGRAM

    HORIE YASUNORI / ASAKAWA MASAMI / SAKASHITA KOICHIRO | Europäisches Patentamt | 2021

    Freier Zugriff