Supporting knowledge elicitation and consensus building for dempster-shafer decision models

Osei-Bryson, Kweku-Muata

doi:10.1002/int.10078

Cited by 15 publications

(5 citation statements)

References 36 publications

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“…Thus, at time t ∈ t, the relevant data vectors c Ψ κ = [ c y κ , c ψ κ ] have the regression vectors c ψ κ , κ ∈ κ, which yield small values of the divergence D tκ (28). The next discussion shows that the term "small" can be well quantified.…”

Section: Real-time Selection Of the Relevant Datamentioning

confidence: 87%

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Fully probabilistic knowledge expression and incorporation

Kárný

Guy

Kracík³

et al. 2014

Statistics and Its Interface

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An exploitation of prior knowledge in parameter estimation becomes vital whenever measured data is not informative enough. Elicitation of quantified prior knowledge is a well-elaborated art in societal and medical applications but not in the engineering ones. Frequently required involvement of a facilitator is mostly unrealistic due to either facilitator's high costs or complexity of modelled relationships that cannot be grasped by humans. This paper provides a facilitator-free approach based on an advanced knowledgesharing methodology. It presents the approach on commonly available types of knowledge and applies the methodology to a normal controlled autoregressive model.

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Section: Real-time Selection Of the Relevant Datamentioning

confidence: 87%

“…Knowledge elicitation, i.e. mapping of prior knowledge onto the prior pdf is supported by a range of techniques [28,12]. They generally rely on a facilitator, who guides the knowledge provider and quantifies knowledge gathered.…”

Section: Introductionmentioning

confidence: 99%

Fully probabilistic knowledge expression and incorporation

Kárný

Guy

Kracík³

et al. 2014

Statistics and Its Interface

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“…Another major issue with the methods applied in this study is subjectivity, particularly with regards to defining the weights in the WLC models, and the basic probability assignments in the DST analysis. A number of sources of information may be utilised for these purposes, including expert opinion [8], statistical data and published literature [13]. In our WLC analysis we derived crude weights according to the relative frequency by which each factor was mentioned in the published literature.…”

Section: Discussionmentioning

confidence: 99%

Untitled

2006

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BackgroundThere are few studies that have investigated uncertainties surrounding the scientific community's knowledge of the geographical distribution of major animal diseases. This is particularly relevant to Rift Valley fever (RVF), a zoonotic disease causing destructive outbreaks in livestock and man, as the geographical range of the disease is widening to involve previously unaffected regions. In the current study we investigate the application of methods developed in the decision sciences: multiple criteria decision making using weighted linear combination and ordered weighted averages, and Dempster-Shafer theory, implemented within the geographical information system IDRISI, to obtain a greater understanding of uncertainty related to the geographical distribution of RVF. The focus is on presenting alternate methods where extensive field data are not available and traditional, model-based approaches to disease mapping are impossible to conduct.ResultsUsing a compensatory multiple criteria decision making model based on weighted linear combination, most of sub-Saharan Africa was suitable for endemic circulation of RVF. In contrast, areas where rivers and lakes traversed semi-arid regions, such as those bordering the Sahara, were highly suitable for RVF epidemics and wet, tropical areas of central Africa had low suitability. Using a moderately non-compensatory model based on ordered weighted averages, the areas considered suitable for endemic and epidemic RVF were more restricted. Varying the relative weights of the different factors in the models did not affect suitability estimates to a large degree, but variations in model structure had a large impact on our suitability estimates. Our Dempster-Shafer analysis supported the belief that a range of semi-arid areas were suitable for RVF epidemics and the plausibility that many other areas of the continent were suitable. Areas where high levels of uncertainty were highlighted included the Ethiopian Highlands, southwest Kenya and parts of West Africa.ConclusionWe have demonstrated the potential of methods developed in the decision sciences to improve our understanding of uncertainties surrounding the geographical distribution of animal diseases, particularly where information is sparse, and encourage wider application of the decision science methodology in the field of animal health.

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“…If η = 1, then we analyze only belief functions and make pessimistic decision. This type of decision is very often used [1,11]. If η = 0, then we analyze only plausibility functions and make optimistic decision.…”

Section: Comparison With the Whole Set Of Alternativesmentioning

confidence: 99%

A new ranking procedure by incomplete pairwise comparisons using preference subsets

Utkin

2009

IDA

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A method for ranking of alternatives or objects and its extensions by incomplete pairwise comparisons using random set theory are proposed in the paper. The main feature of the method is that it allows us to deal with comparisons of arbitrary groups of alternatives. The method is extended on the case of independent groups of experts. The imprecise Dirichlet model is also used to make cautious decisions in several cases. Various numerical examples illustrate the proposed method and its extensions.

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Supporting knowledge elicitation and consensus building for dempster-shafer decision models

Cited by 15 publications

References 36 publications

Fully probabilistic knowledge expression and incorporation

Fully probabilistic knowledge expression and incorporation

Untitled

A new ranking procedure by incomplete pairwise comparisons using preference subsets

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