Numerical methods for interval and fuzzy number comparison based on the probabilistic approach and Dempster–Shafer theory

Sevastianov, P.

doi:10.1016/j.ins.2007.05.001

Cited by 101 publications

(48 citation statements)

References 38 publications

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“…Each of these orderings admits a characterization in terms of lower or upper expectations, generalizing a corresponding result in the case of stochastic ordering and standard expectation. Note that the approach described here is quite different from that presented in [25], where Dempster-Shafer theory is used to compare real intervals or fuzzy numbers, and the result of the comparison is given in the form of a belief interval or a fuzzy number. The problem of finding the least committed belief function subject to a credal ordering constraint has then been studied in detail for each of the four basic credal orderings.…”

Section: Discussionmentioning

confidence: 99%

Extending stochastic ordering to belief functions on the real line

Denux

2009

Information Sciences

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In this paper, the concept of stochastic ordering is extended to belief functions on the real line defined by random closed intervals. In this context, the usual stochastic ordering is shown to break down into four distinct ordering relations, called credal orderings, which correspond to the four basic ordering structures between intervals. These orderings are characterized in terms of lower and upper expectations. We then derive the expressions of the least committed (least informative) belief function credally less (respectively, greater) than or equal to a given belief function. In each case, the solution is a consonant belief function that can be described by a possibility distribution. A simple application to reliability analysis is used as an example throughout the paper.

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Section: Discussionmentioning

confidence: 99%

Extending stochastic ordering to belief functions on the real line

Denux

2009

Information Sciences

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“…With all the other factors unchanged, one single factor's interval number (range of fluctuation) is used to calculate the result's interval number, which reflects how the target value changes when this factor varies. Drawing on the interval number comparison and sorting method [12][13][14][15][16], the index calculation method to evaluate and measure the factors importance is defined, through which the quantitative evaluation standard can be got. This method not only takes into account the value zoom in and out led by the mathematical formula itself in the calculation process but also considers the probability distribution of the influencing factor values, which can characterize the factors importance through the results led by the factors comprehensively.…”

Section: Research On Factor Importance Analysis Methodsmentioning

confidence: 99%

Analysis Method Research on the Importance of the Factors Influencing the Flow Safety of Heated Crude Pipelines

Duan

Xiao

et al. 2014

Advances in Mechanical Engineering

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Analyzing the importance of the factors which influence the flow safety of the heated oil pipeline is an important part of the whole assessment process, which is of great significance on the results analysis, phenomenon explanation, and risk control after the assessment. Focusing on the problems in the influencing factors' importance analysis on crude oil pipeline flow assurance assessment, a new method to analyze the importance of the influencing factors is proposed which considers the factors' fluctuations. Based on the actual probability distribution of the influencing factors during the stable operation of the pipeline, a new measure standard of the factors' importance is defined which can measure different factors importance and realize the importance sorting of each factor. The influence of different factors on the inlet temperature is taken as an example. The importance analysis and sensitivity analysis of the influencing factors on the actual pipeline have been done, the results of which are also compared. The results show that this method can combine the pipeline actual operating conditions and the influencing factors' actual fluctuation, reflecting the effect on the results' importance in different values of each factor and different fluctuation. This method can make comprehensive analysis on the importance of the influencing factors effectively.

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“…In this study, the fuzzy DEMATEL approach has been integrated with the Dempster-Shafer theory for evaluation of KT effectiveness from the perspective of GSD teams' via IFNs is Dempster-Shafer in defuzzification process [12,17]. In Dempster-Shafer theory, the information from each source is seen as a piece of evidences which is represented by a basic probability assignment (BPA) [12].…”

Section: Theoretical Foundationsmentioning

confidence: 99%

A fuzzy DEMATEL approach based on intuitionistic fuzzy information for evaluating knowledge transfer effectiveness in GSD projects

Sangaiah

Gao

Ramachandran

et al. 2015

IJICA

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The offshore/onsite teams' effectiveness of knowledge transfer is significantly measured by a various kinds of factors. In this paper, we propose a Knowledge Transfer (KT) assessment framework which is integrates four criterions: knowledge, team, technology, and organization factors to evaluate KT effectiveness of GSD teams. In this context, we presents fuzzy DEMATEL approach for assessing GSD teams KT effectiveness based on intuitionistic fuzzy numbers (IFNs). In this approach, decision makers provided their subjective judgments on the criteria, characterized on the basis of intuitionistic fuzzy sets. Moreover, intuitionistic fuzzy sets are used in the fuzzy DEMATEL approach can be effectively assessing the KT effectiveness criteria, rank the alternatives. Subsequently, the complete process is illustrated with GSD teams' KT evaluation criteria samples, the factors are ranked using fuzzy linguistic variables which are mapped to IFNs. In that case, IFNs has been converted into their corresponding basic probability assignments (BPAs) and then Dempster-Shafer theory is used to combine the group decision making process. Besides, illustrate applicability and usefulness of proposed approach in group decision making process for evaluation of multiple criteria's under fuzzy environment has been tested by software professionals at Inowits software organization in India.

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Numerical methods for interval and fuzzy number comparison based on the probabilistic approach and Dempster–Shafer theory

Cited by 101 publications

References 38 publications

Extending stochastic ordering to belief functions on the real line

Extending stochastic ordering to belief functions on the real line

Analysis Method Research on the Importance of the Factors Influencing the Flow Safety of Heated Crude Pipelines

A fuzzy DEMATEL approach based on intuitionistic fuzzy information for evaluating knowledge transfer effectiveness in GSD projects

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