• DocumentCode
    3019208
  • Title

    Displacement back analysis on supporting structure of deep foundation pit based on evolutionary neural nrtwork

  • Author

    Zhao, Sheng-Li ; Liu, Yan

  • Author_Institution
    Rural & Urban Constr. Coll., Hebei Agric. Univ., Baoding, China
  • fYear
    2009
  • fDate
    12-15 July 2009
  • Firstpage
    171
  • Lastpage
    174
  • Abstract
    An evolutionary neural network method of displacement back analysis on supporting structure of deep foundation pit is proposed to search the optimal mechanical parameters. First, the BP network replaces the time-consuming finite element method to establish the non-linear relationship between the values of deep foundation pit mechanical parameters and displacement of its supporting structure, then genetic algorithm is used as an optimization method to search the optimal mechanical parameters in their global ranges. Application of this methodology is illustrated with a numerical example and reasonable results are yielded.
  • Keywords
    backpropagation; foundations; genetic algorithms; geotechnical engineering; neural nets; structural engineering computing; supports; BP network; deep foundation pit; displacement back analysis; evolutionary neural network; genetic algorithm; optimal mechanical parameter; optimization; supporting structure; Algorithm design and analysis; Educational institutions; Electronic mail; Finite element methods; Genetic algorithms; Neural networks; Optimization methods; Pattern analysis; Pattern recognition; Wavelet analysis; BP network; Displacement back analysis; Genetic algorithm; Supporting structure of deep foundation pit;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Wavelet Analysis and Pattern Recognition, 2009. ICWAPR 2009. International Conference on
  • Conference_Location
    Baoding
  • Print_ISBN
    978-1-4244-3728-3
  • Electronic_ISBN
    978-1-4244-3729-0
  • Type

    conf

  • DOI
    10.1109/ICWAPR.2009.5207405
  • Filename
    5207405