• DocumentCode
    1889365
  • Title

    An Improved Algorithm of Structure Learning Applied in Organizational Factors Bayesian Belief Network

  • Author

    Yu Tonglan ; Li, Zhang

  • Author_Institution
    Sch. of Comput. Sci. & Technol., Univ. of South China, Hengyang, China
  • fYear
    2010
  • fDate
    25-26 Dec. 2010
  • Firstpage
    1
  • Lastpage
    4
  • Abstract
    The paper first introduces the concept of organizational factors in the socio-technical system and the basic theory of Bayesian Network and then discusses the algorithm of structure learning of Bayesian network. A new algorithm base on dependency analysis is proposed to effectively reduce the number of detecting condition independence. It uses heuristic cutset searching algorithm and orients all the edges in the network before removing superfluous edges. Experiment results indicate that it outperforms the traditional algorithm. Finally, organizational factors Bayesian network is constructed by using the algorithm which is helpful for the nuclear pant to discover the critical factors influencing human reliability in nuclear power plant.
  • Keywords
    belief networks; human factors; learning (artificial intelligence); nuclear engineering computing; nuclear power stations; organisational aspects; dependency analysis; heuristic cutset searching algorithm; human reliability; nuclear power plant; organizational factors Bayesian belief network; sociotechnical system; structure learning; Algorithm design and analysis; Bayesian methods; Complexity theory; Humans; Image edge detection; Object oriented modeling; Reliability;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information Engineering and Computer Science (ICIECS), 2010 2nd International Conference on
  • Conference_Location
    Wuhan
  • ISSN
    2156-7379
  • Print_ISBN
    978-1-4244-7939-9
  • Electronic_ISBN
    2156-7379
  • Type

    conf

  • DOI
    10.1109/ICIECS.2010.5677838
  • Filename
    5677838