• DocumentCode
    3224015
  • Title

    Application of BP neural network in the prediction of consolidation coefficient

  • Author

    Zhu, Hong-Hu ; Fu, Jian-Ping ; Dai, Fei

  • Author_Institution
    Dept. of Civil & Struct. Eng., Hong Kong Polytech. Univ., Hong Kong, China
  • fYear
    2009
  • fDate
    15-17 July 2009
  • Firstpage
    443
  • Lastpage
    446
  • Abstract
    The application of artificial neural network (ANN) in the discipline of geotechnical engineering is discussed in this paper. A multi-layer error back-propagation (BP) feed-forward neural network model was proposed to predict an important geotechnical parameter, namely the consolidation coefficient. The conventional methods for predicting consolidation coefficient is briefly introduced. Based on the results of laboratory consolidation tests, the BP model was trained and used to determine the consolidation coefficient. The predicted values were compared to those determined by graphical methods. It is proved that the BP neural network approach yielded similar results compared with other methods.
  • Keywords
    backpropagation; feedforward neural nets; geophysics computing; geotechnical engineering; graph theory; BP neural network; artificial neural network; consolidation coefficient prediction; feed-forward neural network model; geotechnical engineering; graphical methods; multilayer error back-propagation neural network model; Artificial neural networks; Biological neural networks; Feedforward neural networks; Feedforward systems; Hydrogen; Laboratories; Multi-layer neural network; Neural networks; Predictive models; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on
  • Conference_Location
    Zouk Mosbeh
  • Print_ISBN
    978-1-4244-3833-4
  • Electronic_ISBN
    978-1-4244-3834-1
  • Type

    conf

  • DOI
    10.1109/ACTEA.2009.5227942
  • Filename
    5227942