• DocumentCode
    510053
  • Title

    Artificial Neural Network´s Application in Intelligent Prediction of Enclosure Structure Deformation Induced by Foundation Pit Excavation

  • Author

    Chen Haiming ; Zhou Shengquan ; Yang Zhao ; Liu Cheng

  • Author_Institution
    Sch. of Civil Eng. & Archit., Anhui Univ. of Sci. & Technol., Huainan, China
  • Volume
    2
  • fYear
    2009
  • fDate
    7-8 Nov. 2009
  • Firstpage
    507
  • Lastpage
    510
  • Abstract
    Enclosure structure deformation induced by foundation pit excavation is one of important problems in foundation pit engineering. The factors influencing the enclosure structure deformation are complex and have stochastic and fuzzy properties, which have brought difficulties to the enclosure structure deformation prediction. The traditional methods are obviously inadequate while being used to predict the enclosure structure deformation. In this paper, the intelligent prediction method based on BP artificial neural network (ANN) and multi-step circulation is established and can solve these problems. Practices show that the accuracy of the method can meet the application requirements; the method has a few features, such as, with high efficiency, use of convenience, suitable for engineering applications, and so on, and has certain engineering and technical value.
  • Keywords
    backpropagation; deformation; foundations; neural nets; structural engineering computing; BP artificial neural network; enclosure structure deformation prediction; foundation pit engineering; foundation pit excavation; fuzzy properties; intelligent prediction method; stochastic properties; Artificial intelligence; Artificial neural networks; Competitive intelligence; Design engineering; Electronic mail; Intelligent networks; Intelligent structures; Intelligent systems; Monitoring; Prediction methods; ANN; foundation pit; intelligent predication; multi-step circulation;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Artificial Intelligence and Computational Intelligence, 2009. AICI '09. International Conference on
  • Conference_Location
    Shanghai
  • Print_ISBN
    978-1-4244-3835-8
  • Electronic_ISBN
    978-0-7695-3816-7
  • Type

    conf

  • DOI
    10.1109/AICI.2009.375
  • Filename
    5375890