• DocumentCode
    1752761
  • Title

    Causality Diagram using Triangular Fuzzy Numbers

  • Author

    Liang, Xinyuan

  • Author_Institution
    Dept. of Comput., Chongqing Technol. & Bus. Univ.
  • Volume
    1
  • fYear
    0
  • fDate
    0-0 0
  • Firstpage
    2503
  • Lastpage
    2507
  • Abstract
    Fuzzy concepts are introduced to replace probabilistic considerations in the causality diagram by the possibilistic ones and to reduce the difficulty arising from the inexact and insufficient information of the distribution functions of basic event and linkage event. All events are considered as fuzzy numbers, and n-ary fuzzy AND and OR operators are used to evaluate the possibility of system events failure. Fuzzy causality diagram (FCD) is so effective in fault analysis, and it is more flexible and adaptive than conventional causality diagram. However, the shortcoming in FCD is that the result, i.e. fuzzy numbers, may go beyond interval [0,1], A normalization algorithm was proposed to solve the problem. The research indicates that the normalization method is so practical that the result of reasoning coincides with that of conventional causality diagram. The research can be of considerable importance for fault analysis of complex and hazardous industrial systems
  • Keywords
    causality; diagrams; fuzzy reasoning; possibility theory; causality diagram; distribution functions; fuzzy operators; normalization algorithm; triangular fuzzy numbers; Business communication; Computer science; Computer science education; Couplings; Distribution functions; Educational programs; Fuzzy reasoning; Fuzzy systems; Hazards; Humans; Causality Diagram (CD); Fault Analysis (FA); Fuzzy Numbers (FN); Triangular Fuzzy Number (TFN);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Intelligent Control and Automation, 2006. WCICA 2006. The Sixth World Congress on
  • Conference_Location
    Dalian
  • Print_ISBN
    1-4244-0332-4
  • Type

    conf

  • DOI
    10.1109/WCICA.2006.1712812
  • Filename
    1712812