• DocumentCode
    620064
  • Title

    Operational ability evaluation model of the armored weapon system of system

  • Author

    Zuo Xuesheng ; Qu Yang

  • Author_Institution
    Armored Inst., Bengbu, China
  • fYear
    2013
  • fDate
    25-27 May 2013
  • Firstpage
    2161
  • Lastpage
    2163
  • Abstract
    On the basis of taking the weapon system of system operational ability evaluation indexes for reference, we combine with the character of the armored weapon , seek advice from experts, and built the armored weapon operational ability evaluation indexes system. Then, we take the building train samples and experts marking samples to train the BP neural networks, and evaluate the armored weapon system of system operational ability. The results indicate the trained neural network is reasonable to evaluate the operational ability. It could reduce the artificial factor, and make the results more reliable. The model could take reference for the operational evaluation to the armored weapon system of system.
  • Keywords
    armour; backpropagation; military computing; neural nets; weapons; BP neural network; armored weapon system of system; artificial factor; building train sample; experts marking sample; operational ability evaluation model; system operational ability evaluation index; trained neural network; Biological neural networks; Indexes; Modeling; Training; Weapons; Armored weapon SOS; Evaluation; Neural Network; Operational Ability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Control and Decision Conference (CCDC), 2013 25th Chinese
  • Conference_Location
    Guiyang
  • Print_ISBN
    978-1-4673-5533-9
  • Type

    conf

  • DOI
    10.1109/CCDC.2013.6561293
  • Filename
    6561293