Dependence assessment in human reliability analysis based on evidence credibility decay model and IOWA operator

Zheng, Xuemei; Deng, Yong

doi:10.1016/j.anucene.2017.10.045

Cited by 80 publications

(42 citation statements)

References 47 publications

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“…Furthermore,

0true F ((), a_{1}, a_{2}, \dots, a_{n}) = \sum_{j} w_{j} b_{j}

where

b_{j}

is the j th largest of the

a_{i}

. OWA operator is a simple and effective aggregating formulation in the data fusion, which has been applied in many applications, such as aggregating probability distribution, multicriteria decision making, emission control in green engineering, and complex network analysis …”

Section: Preliminariesmentioning

confidence: 99%

Generating Z-number based on OWA weights using maximum entropy

Kang

Deng

Hewage

et al. 2018

Int. J. Intell. Syst.

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In the application of Z‐number, how to generate Z‐number is a significant and open issue. In this paper, we proposed a method of generating Z‐number based on the OWA weights using maximum entropy considering the attitude (preference) of the decision maker. Some numerical examples are used to illustrate the effectiveness of the proposed method. Results show that the attitude (preference) of the decision maker can give an optimal possibility distribution of the reliability for Z‐number using maximum entropy.

show abstract

“…Furthermore,

0true F ((), a_{1}, a_{2}, \dots, a_{n}) = \sum_{j} w_{j} b_{j}

where

b_{j}

is the j th largest of the

a_{i}

Section: Preliminariesmentioning

confidence: 99%

Generating Z-number based on OWA weights using maximum entropy

Kang

Deng

Hewage

et al. 2018

Int. J. Intell. Syst.

Self Cite

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“…Because of its reliability, safety, and simplicity, FMEA plays an important role in the design of industrial products such as structures operating in power, aeronautics, and astronautics . Failure mode and effects analysis can be a solution for various reliability problems in many industries including aerospace, nuclear, chemical, and manufacturing …”

Section: Introductionmentioning

confidence: 99%

Failure mode and effects analysis based on D numbers and TOPSIS

Bian

Zheng

Yin

et al. 2018

Quality & Reliability Eng

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175

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Failure mode and effects analysis (FMEA) is a widely used technique for assessing the risk of potential failure modes in designs, products, processes, system, and services. One of the main problems with FMEA is the need to address a variety of assessments given by FMEA team members and the sequence of the failure modes according to the degree of risk factors. Many different methods have been proposed to improve the traditional FMEA, which is impractical when the risk assessments given by multiple experts to one failure mode are imprecise, incomplete, or inconsistent. However, the existing methods cannot adequately handle these types of uncertainties. In this paper, a new risk priority model based on D numbers and technique for the order of preference by similarity to ideal solution (TOPSIS) is proposed to evaluate the risk in FMEA. In the proposed model, the assessments given by the FMEA team members are represented by D numbers, where a new feasible and effective method can effectively represent the uncertain information. The TOPSIS method, a multicriteria decision‐making method is presented to rank the preference of failure modes with respect to risk factors. Finally, an application of the failure modes of the rotor blades of an aircraft turbine is provided to illustrate the efficiency of the proposed method.

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“…Information fusion is to detect, combine, correlate, estimate, and combine multisource data to achieve accurate state estimation and identity estimation. Information fusion technology is widely used in reliability analysis, image processing, intelligent transportation systems, and so on. The advantages of information fusion can be summarized as follows: The information fusion system fuses the information from different sources and overcomes the one‐sidedness of the single information source.…”

Section: Introductionmentioning

confidence: 99%

An improved soft likelihood function for Dempster-Shafer belief structures

Jiang

2018

Int. J. Intell. Syst.

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Information fusion is an important research direction. In the field of information fusion, there are many methods for evidence combination. Recently, Yager proposed a method of soft likelihood function to combine probabilistic evidence effectively. Considering that basic probability assignment (BPA) can deal with uncertainty information more effectively, in this paper, we extend Yager's soft likelihood function to combine BPA. First, according to the BPA evaluations of evidence sources, belief function and plausibility function on each alternative are calculated. Then, interval numbers are constructed by the obtained belief function and plausibility function to indicate the belief interval on each alternative. Next, the descending sorting of interval numbers is aggregated by the ordered weighted averaging operator. Finally, by sorting the result of the aggregation, the ordering of alternatives is obtained. A numerical example and an example of application in Iris data set classification illustrate the effectiveness of the improved method.

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Dependence assessment in human reliability analysis based on evidence credibility decay model and IOWA operator

Cited by 80 publications

References 47 publications

Generating Z-number based on OWA weights using maximum entropy

Generating Z-number based on OWA weights using maximum entropy

Failure mode and effects analysis based on D numbers and TOPSIS

An improved soft likelihood function for Dempster-Shafer belief structures

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