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Dempster-Shafer evidence theory (DST) is a theoretical framework for uncertainty modeling and reasoning. The determination of basic belief assignment (BBA) is crucial in DST, however, there is no general theoretical method for BBA determination. In this paper, a method of generating BBA using fuzzy numbers is proposed. First, the training data are modeled as fuzzy numbers. Then, the dissimilarities...
The theory of belief functions is a very appealing theory for uncertainty modeling and reasoning which has been widely used in information fusion. However, when the cardinality of the frame of discernment and the number of the focal elements are large the fusion of belief functions requires in general a high computational complexity. To circumvent this difficulty, many methods were proposed to implement...
The dissimilarity of evidence, which represent the degree of dissimilarity between bodies of evidence (BOE's), has attracted more and more research interests and has been used in many applications based on evidence theory. In this paper, some novel dissimilarities of evidence are proposed by using fuzzy sets theory (FST). The basic belief assignments (bba's) are first transformed to the measures in...
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