• DocumentCode
    3383243
  • Title

    A fuzzy dynamic bayesian network-based situation assessment approach

  • Author

    Naderpour, M. ; Jie Lu ; Guangquan Zhang

  • Author_Institution
    Centre for Quantum Comput. & Intell. Syst., Univ. of Technol., Sydney, NSW, Australia
  • fYear
    2013
  • fDate
    7-10 July 2013
  • Firstpage
    1
  • Lastpage
    8
  • Abstract
    Situation awareness (SA), a state in the mind of a human, is essential to conduct decision-making activities. It is about the perception of the elements in the environment, the comprehension of their meaning, and the projection of their status in the near future. Two decades of investigation and analysis of accidents have showed that SA was behind of many serious large-scale technological systems´ accidents. This emphasizes the importance of SA support systems development for complex and dynamic environments. This paper presents a fuzzy dynamic Bayesian network-based situation assessment approach to support the operators in decision making process in hazardous situations. The approach includes a dynamic Bayesian network-based situational network to model the hazardous situations where the existence of the situations can be inferred by sensor observations through the SCADA monitoring system using a fuzzy quantizer method. In addition to generate the assessment result, a fuzzy risk estimation method is proposed to show the risk level of situations. Ultimately a hazardous environment from U.S. Chemical Safety Board investigation reports has been used to illustrate the application of proposed approach.
  • Keywords
    SCADA systems; belief networks; decision making; estimation theory; fuzzy set theory; risk management; SA support systems development; SCADA monitoring system; U.S. Chemical Safety Board investigation reports; assessment result; complex environment; decision making process; decision-making activity; dynamic Bayesian network-based situational network; dynamic environment; fuzzy dynamic Bayesian network-based situation assessment approach; fuzzy quantizer method; fuzzy risk estimation method; hazardous environment; hazardous situations; large-scale technological systems accidents; sensor observations; situation awareness; Accidents; Bayes methods; Estimation; Fuzzy logic; Monitoring; Random variables; Safety; dynamic Bayesian network; fuzzy sets; situation assessment; situation awareness;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Fuzzy Systems (FUZZ), 2013 IEEE International Conference on
  • Conference_Location
    Hyderabad
  • ISSN
    1098-7584
  • Print_ISBN
    978-1-4799-0020-6
  • Type

    conf

  • DOI
    10.1109/FUZZ-IEEE.2013.6622430
  • Filename
    6622430