• DocumentCode
    2229402
  • Title

    Analyzing multi-story buildings using hopfield neural network

  • Author

    Fakhrmoosavi, Seyyedeh Hoora ; Setayeshi, Saeed ; Mohammadi, Seyyed Davood Ojaghzadeh ; Bahar, Arash ; Beik, Hossein Arab Ali

  • Author_Institution
    Dept. of Comput. Eng., Islamic Azad Univ., Tehran, Iran
  • Volume
    3
  • fYear
    2010
  • fDate
    20-22 Aug. 2010
  • Abstract
    A simplified method based on neural network is presented to determine the displacements, forces and moments of a loaded structure. Different values of loads, bay length, and story height can be applied to the structure. The results are used for preliminary design of structure, although in many cases the difference between the results obtained by this approach and exact values can be ignored. Thus, the cost of design, which is due to iterative procedure of finding forces and determining the size of members, will be decreased significantly. Obtained results for a sample structure are compared with exact values.
  • Keywords
    CAD; Hopfield neural nets; structural engineering computing; Hopfield neural network; design; multistory buildings; structural loads; structure bay length; Bismuth; Content addressable memory; Hopfield network; Neural Network; multi-story building; preliminary design;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Advanced Computer Theory and Engineering (ICACTE), 2010 3rd International Conference on
  • Conference_Location
    Chengdu
  • ISSN
    2154-7491
  • Print_ISBN
    978-1-4244-6539-2
  • Type

    conf

  • DOI
    10.1109/ICACTE.2010.5579584
  • Filename
    5579584