NDLI: Causality diagram using normal fuzzy numbers

Content Provider	IEEE Xplore Digital Library
Author	Shi Qingxi Liang Xinyuan Zhang Qin
Copyright Year	2005
Description	Author affiliation: Coll. of Autom., Chongqing Univ., China (Shi Qingxi)
Abstract	This paper applies fuzzy concepts to causality diagram, where the probabilities of all events are considered as fuzzy numbers, and shows that n-ary fuzzy AND and OR operators are used to evaluate the possibility of system events failure. A normal fuzzy number (NFN) can be defined completely by a triplet (m, /spl alpha/, /spl beta/). We can diagnose system fault based on fuzzy probability of the events. The goal of this paper is to replace probabilistic considerations in the causality diagram by the probabilistic ones and to reduce the difficulty arising from the inexact and insufficient information of the distribution functions of basic event and linkage event. The result of numerical simulating is coincident with the fact, so the fuzzy causality diagram is effective. The research indicates that fuzzy causality diagram is so effective in fault analysis, and it is more flexible and adaptive than conventional causality diagram.
Sponsorship	IEEE Comput. Intelligence Soc
Starting Page	221
Ending Page	224
File Size	804136
Page Count	4
File Format	PDF
ISBN	0780390172
DOI	10.1109/GRC.2005.1547271
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-07-25
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Educational programs Normal Fuzzy Number (NFN) Humans Educational institutions Hazards Fault Analysis Couplings Causality Diagram Fuzzy Number Numerical simulation Computer science education Fuzzy systems Accidents Distribution functions
Content Type	Text
Resource Type	Article

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