Embankment settlement prediction and control is one of the most critical problems for constructing and maintaining the High-speed railway (HSR). The grey model is one of the popular methods used for predicting embankment settlement, because it is of easy-to-use and low computer load. However, it needs many observations and more suit for short-term prediction. The artificial neural network has been widely used in prediction system in many other fields, and it is of robustness and self-adaptive. In this paper, these two methods are combined to give a new Hybrid prediction model to improve the performance and precision of settlement prediction model. The experiments based on real data sets validate the proposed method.


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    Titel :

    Hybrid Prediction Model for High-Speed Railway Embankment Settlement Using Grey Artificial Neural Network


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Ni, Yi-Qing (Herausgeber:in) / Ye, Xiao-Wei (Herausgeber:in) / Zhang, T. G. (Autor:in) / Hu, Z. B. (Autor:in) / Yang, C. F. (Autor:in) / Liu, Y. (Autor:in)


    Erscheinungsdatum :

    2012-01-01


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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