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
Link To Document