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Using Belief Functions to forecast demand for Mobile Satellite Services
 Belief Functions in Business Decisions
, 2002
"... Abstract. This paper outlines an application of belief functions to forecasting the demand for a new service in a new category, based on new technology. Forecasting demand for a new product or service is always diÆcult. It is more so when the product category itself is new, and so unfamiliar to pote ..."
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Cited by 11 (8 self)
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Abstract. This paper outlines an application of belief functions to forecasting the demand for a new service in a new category, based on new technology. Forecasting demand for a new product or service is always diÆcult. It is more so when the product category itself is new, and so unfamiliar to potential consumers, and the quality of service of the product is dependent upon a new technology whose actual performance quality is not known in advance. In such a situation, market research is often unreliable, and so the beliefs of key stakeholders regarding the true values of underlying variables typically vary considerably. Belief functions provide a means of representing and combining these varied beliefs which is more expressive than traditional point probability estimates. 1
A Rough Set Approach to Reasoning Under Uncertainty
, 1995
"... This paper presents an introduction to various forms of reasoning under uncertainty that are based on rough sets. In particular, a number of sets of numerical and symbolic truth values which may be used to augment propositional logic are developed, and a semantics for these values is provided ba ..."
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Cited by 7 (6 self)
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This paper presents an introduction to various forms of reasoning under uncertainty that are based on rough sets. In particular, a number of sets of numerical and symbolic truth values which may be used to augment propositional logic are developed, and a semantics for these values is provided based upon the notion of possible worlds. Methods of combining the truth values are developed so that they may be propagated when augmented logic formulee are combined, and their use is demonstrated in theorem proving
© Springer Science+Business Media, LLC 2009
, 2009
"... Abstract In this paper, we present a new 2tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitative information using fusion rules drawn from DezertSmarandache Theory (DSmT) framework. Such new approach allows to preserve the precision and ..."
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Abstract In this paper, we present a new 2tuple linguistic representation model, i.e. Distribution Function Model (DFM), for combining imprecise qualitative information using fusion rules drawn from DezertSmarandache Theory (DSmT) framework. Such new approach allows to preserve the precision and efficiency of the combination of linguistic information in the case of either equidistant or unbalanced label model. Some basic operators on imprecise 2tuple labels are presented together with their extensions for imprecise 2tuple labels. We also give simple examples to show how precise and imprecise qualitative information can be combined for reasoning under uncertainty. It is concluded that DSmT can deal efficiently with both precise and imprecise quantitative and qualitative beliefs, which extends the scope of this theory.
representation model, i.e. Distribution Function Model
, 2009
"... Abstract In this paper, we present a new 2tuple linguistic ..."
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Fusion of qualitative beliefs using DSmT
, 2006
"... Abstract – This paper introduces the notion of qualitative belief assignment to model beliefs of human experts expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined using an extension of DezertSmarandache Theory (DSmT) of plausible and p ..."
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Abstract – This paper introduces the notion of qualitative belief assignment to model beliefs of human experts expressed in natural language (with linguistic labels). We show how qualitative beliefs can be efficiently combined using an extension of DezertSmarandache Theory (DSmT) of plausible and paradoxical quantitative reasoning to qualitative reasoning. We propose a new arithmetic on linguistic labels which allows a direct extension of classical DSm fusion rule or DSm Hybrid rules. An approximate qualitative PCR5 rule is also proposed jointly with a Qualitative Average Operator. We also show how crisp or interval mappings can be used to deal indirectly with linguistic labels. A very simple example is provided to illustrate our qualitative fusion rules. Keywords: Qualitative Information Fusion, Computing with Words (CW), DezertSmarandache Theory. 1