• DocumentCode
    460670
  • Title

    Study on the Identification of Loading Materials for Initiating Explosive Device

  • Author

    Wang, Yong ; Li, Jianfu

  • Author_Institution
    Dept. of Comput., Chongqing Educ. Coll.
  • Volume
    3
  • fYear
    2006
  • fDate
    25-28 June 2006
  • Firstpage
    2030
  • Lastpage
    2033
  • Abstract
    Neural network (NN) design is a key issue in the study of artificial neural networks. The use of genetic algorithm in searching the best hidden neurons makes the structural modular neural network less likely to be trapped in local minima than the traditional gradient-based search algorithms. Based on the analyses of the pressing model of loading materials for initiating explosive device and the cooperation of computing intelligent theories, an identification system of loading materials for initiating explosive device is developed on neural networks with genetic algorithms. Emphatically the experiment results show the identification requirement of loading materials for initiating explosive device can be satisfied in this system
  • Keywords
    explosives; genetic algorithms; neural nets; search problems; artificial neural networks; explosive device; genetic algorithm; gradient-based search algorithms; loading materials identification; Algorithm design and analysis; Artificial neural networks; Computer networks; Explosives; Genetic algorithms; Intelligent networks; Load modeling; Neural networks; Neurons; Pressing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications, Circuits and Systems Proceedings, 2006 International Conference on
  • Conference_Location
    Guilin
  • Print_ISBN
    0-7803-9584-0
  • Electronic_ISBN
    0-7803-9585-9
  • Type

    conf

  • DOI
    10.1109/ICCCAS.2006.285076
  • Filename
    4064302