• DocumentCode
    2506532
  • Title

    Application of elevator group control system based on genetic algorithm optimize BP fuzzy neural network

  • Author

    Wang, Yanqiu ; Zhang, Jian ; Zhao, Yueling ; Wang, Yu

  • Author_Institution
    Liao Ning Univ. of Technol., Jinzhou
  • fYear
    2008
  • fDate
    25-27 June 2008
  • Firstpage
    8702
  • Lastpage
    8705
  • Abstract
    Its deficiency was revealed because of traffic pattern identification method of elevator group control system based on using BP neural network, and a new traffic patten identification model is proposed which is based on optimizing fuzzy neural network by genetic algorithm. The genetic algorithm is used to train fuzzy BP neural network, which can overcome the shortcoming of local minimum appeared while training the network, and the veracity of the whole traffic pattern identification model can be increased. At last, the sampled data are trained and tested Matlab software, and the simulation results indicate that the proposed identify model has very small error.
  • Keywords
    backpropagation; fuzzy control; fuzzy neural nets; genetic algorithms; lifts; neurocontrollers; BP fuzzy neural network; elevator group control system; genetic algorithm; optimization; traffic pattern identification; Communication system traffic control; Control system synthesis; Control systems; Elevators; Fuzzy control; Fuzzy neural networks; Genetic algorithms; Mathematical model; Neural networks; Traffic control; BP neural network; Elevator Group Control System; fuzzy neural network; genetic algorithm;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2008. WCICA 2008. 7th World Congress on
  • Conference_Location
    Chongqing
  • Print_ISBN
    978-1-4244-2113-8
  • Electronic_ISBN
    978-1-4244-2114-5
  • Type

    conf

  • DOI
    10.1109/WCICA.2008.4594612
  • Filename
    4594612