The Dempster–Shafer theory of evidence: an alternative approach to multicriteria decision modelling

Beynon, Malcolm James; Curry, Bruce; Morgan, Phillip L.

doi:10.1016/s0305-0483(99)00033-x

Cited by 367 publications

(238 citation statements)

References 22 publications

Supporting

Mentioning

221

Contrasting

Unclassified

Order By: Relevance

“…When ignorance has the value of zero, the Dempster-Shafer model is reduced to the standard Bayesian model. Thus, the Dempster-Shafer theory is an attempt to generalize probability theory by introducing a rule for combining distinct bodies of evidence (Beynon et al, 2000); it is thus actually a numerical method of evidential reasoning. Compared with Bayesian theory, evidence theory feels closer to our human perception and reasoning processes.…”

Section: Evidence Theorymentioning

confidence: 99%

Possibility and Evidence-Based Reliability Analysis and Design Optimization

Huang

Liu

et al. 2013

American Journal of Engineering and Applied Sciences

View full text Add to dashboard Cite

Engineering design under uncertainty has gained considerable attention in recent years. A great multitude of new design optimization methodologies and reliability analysis approaches are put forth with the aim of accommodating various uncertainties. Uncertainties in practical engineering applications are commonly classified into two categories, i.e., aleatory uncertainty and epistemic uncertainty. Aleatory uncertainty arises because of unpredictable variation in the performance and processes of systems, it is irreducible even adding more data or knowledge. On the other hand, epistemic uncertainty stems from lack of knowledge of the system due to limited data, measurement limitations, or simplified approximations in modeling system behavior and it can be reduced by obtaining more data or knowledge. More specifically, aleatory uncertainty is naturally represented by a statistical distribution and its associated parameters can be characterized by sufficient data. If, however, the data is limited and can be quantified in a statistical sense, epistemic uncertainty can be considered as an alternative tool in such a situation. Of the several optional treatments for epistemic uncertainty, possibility theory and evidence theory have proved to be the most computationally efficient and stable for reliability analysis and engineering design optimization. This study first attempts to provide a better understanding of uncertainty in engineering design by giving a comprehensive overview of its classifications, theories and design considerations. Then a review is conducted of general topics such as the foundations and applications of possibility theory and evidence theory. This overview includes the most recent results from theoretical research, computational developments and performance improvement of possibility theory and evidence theory with an emphasis on revealing the capability and characteristics of quantifying uncertainty from different perspectives. Possibility and evidence theory-based reliability methods have many advantages for practical engineering when compared with traditional probability-based reliability methods. They can work well under limited data while the latter need large amounts of information, more than possible in engineering practice due to aleatory and epistemic uncertainties. The possible directions for future work are summarized.

show abstract

Section: Evidence Theorymentioning

confidence: 99%

Possibility and Evidence-Based Reliability Analysis and Design Optimization

Huang

Liu

et al. 2013

American Journal of Engineering and Applied Sciences

View full text Add to dashboard Cite

show abstract

“…The rule of combination (equation 10) has also been used for data fusion in different applications (see e.g., Rottensteiner et al 2005;Basir et al 2005;Fan et al 2006). The Theory has also been applied to model multi-criteria decision making (see e.g., Beynon et al 2000;Hua et al 2008). …”

Section: Dempster-shafer Theorymentioning

confidence: 99%

A scoping inquiry into the potential contribution of Subjective Probability Theory, Dempster–Shafer Theory and Possibility Theory in accommodating degrees of belief in traveller behaviour research

Hensher

2014

Travel Behaviour and Society

View full text Add to dashboard Cite

There is a small but growing interest in traveller behaviour research on investigating ways to identify and quantify degrees of belief (as subjective probabilities or other propositions) associated with behavioural responses, especially in the context of popular travel choice methods such as stated choice experiments, as a way of adding to our understanding of decision making in real-world contexts that are associated with inevitable risk and uncertainty. This paper reviews three major theories that are not well known in the transportation literature that have been developed in psychology and decision sciences to accommodate belief, namely Subjective Probability Theory, Dempster-Shafer Theory and Possibility Theory. We focus on how degrees of belief are measured in these theories. The key elements of each theoretical approach are compared, including their mathematical properties and evidence patterns. Despite their being few applications to date in transportation, the review promotes the relevance of accounting for degrees of belief in travel choice analysis. Keyword: belief, degree of belief, Subjective Probability Theory, Dempster-Shafer Theory, Possibility TheoryAcknowledgment: This study is supported by the Australian Research Council Discovery Program Grant DP110100454 titled "Assessment of the commuter's willingness to pay a congestion charge under alternative pricing regimes and revenue disbursement plans". We also thank two referees and the Becky Loo for comments.

show abstract

“…DST allows certain limitations within the AHP method to be reduced. One criticism of the AHP method is the sheer number of pairwise comparisons to be performed before any rankings can be evaluated [129]. The original 'theory of evidence', created by Dempster [128] was based around Bayesian probability inference (BPI) in that it deals with subjective beliefs and can handle qualitative as well as quantitative data values.…”

Section: Variousmentioning

confidence: 99%

Sustainability assessment approaches for intelligent transport systems: the state of the art

Kolosz

Grant-Muller

2016

IET Intelligent Transport Systems

View full text Add to dashboard Cite

The appraisal of ITS systems has become increasingly important in order to capture their full range of potential impacts. The goal of this paper is therefore to assess the appropriateness of conventional transport appraisal models and tools for this task, particularly in reflecting the environmental and socio-economic impacts of ITS. These include the most common Environmental Systems Analysis tools (ESAT), which incorporate international standards and are of considerable importance in indicating sustainability. A review of how emerging methods relate to the goal of a successful transition to a low carbon future is reported, based on the literature. The appraisal of ITS is inherently uncertain due to the decentralised nature of Information Communication Technology (ICT), therefore a range of methods to capture this aspect are reviewed. The models, weights and methods are analysed concerning their ability to estimate sustainability performance, given the numerous configurations of ubiquitous technology that may comprise ITS services. Weighting methods are important in reflecting perceptions of how sustainability should be assessed. These can be incorporated by identifying, classifying and selecting one or more ESAT's based upon their suitability for a particular application. Finally, recommendations are given on which tools can be integrated to more comprehensively reflect the performance of ITS.

show abstract

The Dempster–Shafer theory of evidence: an alternative approach to multicriteria decision modelling

Cited by 367 publications

References 22 publications

Possibility and Evidence-Based Reliability Analysis and Design Optimization

Possibility and Evidence-Based Reliability Analysis and Design Optimization

A scoping inquiry into the potential contribution of Subjective Probability Theory, Dempster–Shafer Theory and Possibility Theory in accommodating degrees of belief in traveller behaviour research

Sustainability assessment approaches for intelligent transport systems: the state of the art

Contact Info

Product

Resources

About