• DocumentCode
    530648
  • Title

    Key shape recognition algorithm based on genetic neural network

  • Author

    Yang, Hong-Tao ; Li, Hui ; Li, Xiu-Lan ; Zhao, Dan-Dan

  • Author_Institution
    Inst. of Electr. & Electron. Eng., Changchun Univ. of Technol., Changchun, China
  • Volume
    4
  • fYear
    2010
  • fDate
    24-26 Aug. 2010
  • Firstpage
    270
  • Lastpage
    273
  • Abstract
    To avoid the BP (Back-Propagation) Network´s disadvantages of low training speed, prone to trapping in a local optimum and poor capability of global search, this paper establishes the model of key based on generic algorithm with the research on the key shape, by optimizing the initialized weights and threshold of neural network with GA. After the test of the program complied by MATLAB language and the comparison with pure BP algorithm, the results show that the methods suggested by this paper improve both the accuracy of predicting and the rate of convergence.
  • Keywords
    backpropagation; genetic algorithms; neural nets; shape recognition; BP; MATLAB language; backpropagation; generic algorithm; genetic neural network; shape recognition algorithm; Presses; Training; BP Neutral Network; Generic Algorithm; Key shape recognition;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computer, Mechatronics, Control and Electronic Engineering (CMCE), 2010 International Conference on
  • Conference_Location
    Changchun
  • Print_ISBN
    978-1-4244-7957-3
  • Type

    conf

  • DOI
    10.1109/CMCE.2010.5610145
  • Filename
    5610145