• DocumentCode
    2837717
  • Title

    Fencing Training Decision Support System Based on Bayesian Network

  • Author

    Wei, Zhen Gang ; Liu, Feilong ; Wei, Ai Min ; Cui, Xue

  • Author_Institution
    Dept. Comput. Sci. & Technol., Ocean Univ. of China, Qingdao, China
  • fYear
    2009
  • fDate
    11-13 Dec. 2009
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    In order to coordinate with and promote the scientific process of the national fencing team, we developed the decision support system for training. In fencing training, we established a two-way reasoning model based on Bayesian network and found the relationship between training process and physiological indicators. Combined with experienced knowledge and sample data, we did research on knowledge representation, learning methods and reasoning functions of network in this model and ultimately got the formation of a complete set of training process management and analysis system. We took the women´s epee team as experimental data and did performance comparison with the BP neural network method. The experiments showed that the model can provide effective decision support for coaches.
  • Keywords
    Bayes methods; decision support systems; inference mechanisms; knowledge representation; learning (artificial intelligence); physiology; sport; training; Bayesian network; epee team; fencing training decision support system; knowledge representation; learning methods; national fencing team; physiological indicators; reasoning functions; scientific process; two-way reasoning model; Artificial intelligence; Bayesian methods; Biological system modeling; Data mining; Decision support systems; Educational institutions; Knowledge representation; Management training; Optimization methods; Probability distribution;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Computational Intelligence and Software Engineering, 2009. CiSE 2009. International Conference on
  • Conference_Location
    Wuhan
  • Print_ISBN
    978-1-4244-4507-3
  • Electronic_ISBN
    978-1-4244-4507-3
  • Type

    conf

  • DOI
    10.1109/CISE.2009.5364552
  • Filename
    5364552