Generalized basic probability assignments

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Generalized basic probability assignments

Dempster-Shafer theory allows to construct belief functions from (precise) basic probability assignments. The present paper extends this idea substantially. By considering sets of basic probability assignments, an appealing constructive approach to general interval probability (general imprecise probabilities) is achieved, which allows for a very flexible modelling of uncertain knowledge.

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Transformation of basic probability assignments to probabilities based on a new entropy measure

Dempster-Shafer evidence theory is an efficient mathematical tool to deal with uncertain information. In that theory, basic probability assignment (BPA) is the basic element for the expression and inference of uncertainty. Decision-making based on BPA is still an open issue in Dempster-Shafer evidence theory. In this paper, a novel approach of transforming basic probability assignments to proba...

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Some Basic Probability

In the previous section of the notes, we noted that a random experiment was defined by a procedure and an observation, and that the sample set was the set of all possible observations. For the purposes of computing probabilities, it is often convenient to define the observations in such a way that the outcomes can be assumed to be equally probable.1 The advantage of a sample space with equiprob...

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Multiscale probability transformation of basic probability assignment

Decision making is still an open issue in the application of Dempster-Shafer evidence theory. A lot of works have been presented for it. In the transferable belief model (TBM), pignistic probabilities based on the basic probability assignments are used for decision making. In this paper, multiscale probability transformation of basic probability assignment based on the belief function and the p...

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ژورنال

عنوان ژورنال: International Journal of General Systems

سال: 2005

ISSN: 0308-1079,1563-5104

DOI: 10.1080/03081070500190839