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Fuzzy importance in fault tree analysis
Fuzzy Sets and Systems, 1984In fault tree analysis, system success or failure can be described by the state of the top event, which is usually defined by a so-called structure function. In this paper, we attempt to simplify the calculation process of the structure function and to newly define the state of the top event by the membership function, using fuzzy sets theory ...
Hitoshi Furuta, Naruhito Shiraishi
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Fuzzy fault-tree analysis using failure possibility
Microelectronics Reliability, 1993 Abstract In conventional probability-based fault-tree analysis, the vague property in many systems, especially, the man-machine system is often ignored. To overcome this disadvantage, the fuzzy set theory is applied to fault-tree analysis. The failure possibility defined by a triangular fuzzy number on the interval [0,1] is used to characterize the ...
Gin-Shuh Liang, Mao-Jiun J. Wang
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Analysis on Dynamic Fault Tree Based on Fuzzy Set
Applied Mechanics and Materials, 2011 In case of fault tree analysis of large complex system, the probability of bottom event in dynamic fault tree is uncertain in some cases. To address the problem, the paper presented a dynamic fault tree analysis method based on fuzzy set computation. The method separates logic attributes and timing attributes of dynamic logic gates.
Li Ping Yang
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Hybrid fault tree analysis using fuzzy sets
Reliability Engineering & System Safety, 1997 Abstract In conventional fault tree analysis (FTA), the ambiguous and imprecise events such as human errors tend not to be handled effectively. To overcome this disadvantage, a hybrid approach employing fuzzy set evaluation and probabilistic estimation for FTA is proposed to evaluate abnormal events.
Ching-Torng Lin, Mao-Jiun J. Wang
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FuzzyFTA: a fuzzy fault tree system for uncertainty analysis
Annals of Nuclear Energy, 1999 This paper describes a new approach and new computational system, FuzzyFTA, for reliability analysis using fault tree and fuzzy logic. Some measures are defined to determine critical components and the uncertainty contribution of each one to the system.
Antonio C.F. Guimarẽes +1 more
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Fault diagnosis of induction motor based on decision trees and adaptive neuro-fuzzy inference [PDF]
Expert Systems With Applications, 2009 This paper presents a fault diagnosis method based on adaptive neuro-fuzzy inference system (ANFIS) in combination with decision trees. Classification and regression tree (CART) which is one of the decision tree methods is used as a feature selection ...
Van Tung Tran, Andy C C Tan, Bo-Suk Yang
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A comprehensive framework for risk probability assessment of landfill fire incidents using fuzzy fault tree analysis [PDF]
Chemical Engineering Research and Design, 2022 Landfill fire is the most frequent type of incidents in the waste management complexes. This paper presents a new framework for risk probability evaluation of major fires in landfills using the fuzzy fault tree analysis.
Kourosh Behzadian
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Fuzzy Fault Tree Analysis for Structural Safety
Journal of Intelligent & Fuzzy Systems, 1996A tool that can be used to assess structural safety is fault tree analysis (FTA) , which depends primarily on quantitative information. However, in many cases, safety assessment of civil engineering structures is based on subjective judgement. To improve the traditional FTA, the authors use the fuzzy set concept and introduce fuzzy fault tree analysis (
Tomoyuki Fujino, Fabian C. Hadipriono
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Reliability of a Transport Node based on Fuzzy Fault Tree Analysis
2021 IEEE 15th International Symposium on Applied Computational Intelligence and Informatics (SACI), 2021In this work to be introduced a fuzzy fault tree real time algorithm to identify reliability of highly autonomous driving (HAD) redundant system of a traffic node. The fuzzyfication of the fault tree procedure was realized by expressing the basic events with a membership function. Logical gates had to be generalized based on incoming fuzzy events. Node
József Z. Szabó, Péter Bakucz
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Multilevel fault tree analysis using fuzzy numbers
Computers & Operations Research, 1996zbMATH Open Web Interface contents unavailable due to conflicting licenses.
C. E. Kim, Y. J. Ju, M. Gens
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