• DocumentCode
    3312663
  • Title

    Decision Analysis of Combat Effectiveness Based on Rough Set Neural Network

  • Author

    Dong, Chengxi ; Wu, Dewei ; He, Jing

  • Author_Institution
    Telecommun. Eng. Inst., Air Force Eng. Univ., Xi´´an
  • Volume
    7
  • fYear
    2008
  • fDate
    18-20 Oct. 2008
  • Firstpage
    227
  • Lastpage
    231
  • Abstract
    Information reduction function of the rough set theory is used, which can deal with the imprecise, half-baked, inconsistent data, and combines the neural network´s functions of linearity approximate and pattern recognition. Then, the model of rough set neural network is set up in this paper. A decision analysis information table of satellite navigation system combat effectiveness was built. Apply the model of rough set neural network on the decision analysis of satellite navigation system combat effectiveness, and then the satisfactory decision results were obtained. This method offers new method and idea on the decision analysis of combat effectiveness for the half-baked information.
  • Keywords
    approximation theory; decision theory; military communication; military computing; neural nets; pattern classification; rough set theory; satellite navigation; decision analysis information table; decision classification; half-baked information; information reduction function; linearity approximation; neural network function; pattern recognition; rough set theory; satellite navigation system combat effectiveness; Artificial neural networks; Biological neural networks; Computer networks; Data engineering; Information analysis; Military computing; Neural networks; Satellite navigation systems; Set theory; Uncertainty; combat effectiveness; decision analysis; neural network; rough set; satellite navigation system;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Natural Computation, 2008. ICNC '08. Fourth International Conference on
  • Conference_Location
    Jinan
  • Print_ISBN
    978-0-7695-3304-9
  • Type

    conf

  • DOI
    10.1109/ICNC.2008.508
  • Filename
    4667976