Fuzzy Sets in the Evaluation of Reliability

Hryniewicz, Olgierd

doi:10.1007/978-3-540-37372-8_13

Cited by 8 publications

(2 citation statements)

References 53 publications

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“…Using the same segmentation procedures, finally those membership functions chosen are of triangular fuzzy numbers shown below and graphically shown in Fig. 6, to describe basic event qualitative failure possibilities defined in Hryniewicz (2007). The membership functions of triangular fuzzy numbers are given below in Table 7, to describe basic event qualitative failure possibilities.…”

Section: Fuzzificationmentioning

confidence: 99%

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

Rajakarunakaran¹,

Kumar²,

Prabhu

2015

Journal of Loss Prevention in the Process Industries

122

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Section: Fuzzificationmentioning

confidence: 99%

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

Rajakarunakaran¹,

Kumar²,

Prabhu

2015

Journal of Loss Prevention in the Process Industries

122

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“…In 2007, Hryniewicz [16] used the fuzzy triangular numbers to determine the reliability parameters. After that, Karimi et al [17] presented a novel technique related to fuzzy probability.…”

Section: Introductionmentioning

confidence: 99%

Mathematical Modeling and Evaluation of Reliability Parameters Based on Survival Possibilities under Uncertain Environment

Alburaikan¹,

Khalifa²,

Kumar³

et al. 2023

Computer Modeling in Engineering &Amp; Sciences

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In this article, mathematical modeling for the evaluation of reliability is studied using two methods. One of the methods, is developed based on possibility theory. The performance of the reliability of the system is of prime concern. In view of this, the outcomes for the failure are required to evaluate with utmost care. In possibility theory, the reliability information data determined from decision-making experts are subjective. The same method is also related to the survival possibilities as against the survival probabilities. The other method is the one that is developed using the concept of approximation of closed interval including the piecewise quadratic fuzzy numbers. In this method, a decision-making expert is not sure of his/her estimates of the reliability parameters. Numerical experiments are performed to illustrate the efficiency of the suggested methods in this research. In the end, the paper is concluded with some future research directions to be explored for the proposed approach.

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Fuzzy Sets in the Evaluation of Reliability

Cited by 8 publications

References 53 publications

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

Applications of fuzzy faulty tree analysis and expert elicitation for evaluation of risks in LPG refuelling station

Mathematical Modeling and Evaluation of Reliability Parameters Based on Survival Possibilities under Uncertain Environment

Bayes statistical decisions with random fuzzy data—an application in reliability

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