• DocumentCode
    534369
  • Title

    Foundation settlement forecasting using the new BP-Gompertz model

  • Author

    Liang, Haonan ; Qin, Feihu ; Wang, Jiehao ; Zhang, Tian ; Liang, Yan

  • Author_Institution
    Sch. of Mech. & Civil Eng., China Univ. of Min. & Technol., Xuzhou, China
  • Volume
    1
  • fYear
    2010
  • fDate
    18-19 Oct. 2010
  • Abstract
    In view of each advantages of Gompertz and BP neural network, the Gompertz growth curve model was combined with BP neural network. The BP-Gompertz foundation forecasting model was proposed through using the capability of approximating the true value of BP neural network to optimize the curve fitting capability of Gompertz. An example shows that compared with the traditional Gompertz model, the prediction accuracy of the new BP-Gompertz model is significantly improved. The model provides a new method for the foundation settlement prediction.
  • Keywords
    approximation theory; backpropagation; curve fitting; foundations; neural nets; optimisation; structural engineering computing; BP neural network; BP-Gompertz Model; Gompertz growth curve model; curve fitting capability; foundation settlement forecasting; prediction accuracy; Computer languages; Measurement uncertainty; Time measurement; BP neural network; BP-Gompertz model; Gompertz growth curve model; foundation settlement;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Networking and Automation (ICINA), 2010 International Conference on
  • Conference_Location
    Kunming
  • Print_ISBN
    978-1-4244-8104-0
  • Electronic_ISBN
    978-1-4244-8106-4
  • Type

    conf

  • DOI
    10.1109/ICINA.2010.5636420
  • Filename
    5636420