• DocumentCode
    2811163
  • Title

    Notice of Retraction
    Damage identification of a concrete cantilever beam based on Elman neural network

  • Author

    Zhao Yu ; Zhang Jianwei

  • Author_Institution
    North China Univ. of Water Conservancy & Electr. Power, Zhengzhou, China
  • Volume
    1
  • fYear
    2010
  • fDate
    22-24 Oct. 2010
  • Abstract
    Notice of Retraction

    After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.

    We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.

    The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.

    Elman neural network is presented to identify and locate the crack damage of concrete structures in this paper. A cantilever is analyzed by finite element method, and the damage indices of the perfect structure and damaged structure are gained. Then Elman neural network is used to analyze the single damage and multi-damage quantification and damage location. Numerical simulation results show that Elman neural network method can make a better diagnosis for single and multiple damage identification. This method has certain guiding sense to damage identification in actual structures.
  • Keywords
    beams (structures); cantilevers; concrete; cracks; finite element analysis; neural nets; structural engineering computing; Elman neural network; concrete cantilever beam; crack damage; damage identification; damage location; finite element method; multidamage quantification; Training; Elman neural network; concrete cantilever beam; damage identification; simulation analysis;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer Application and System Modeling (ICCASM), 2010 International Conference on
  • Conference_Location
    Taiyuan
  • Print_ISBN
    978-1-4244-7235-2
  • Type

    conf

  • DOI
    10.1109/ICCASM.2010.5619132
  • Filename
    5619132