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On a Special Class of Dempster-Shafer Theories
2004In this paper we want to draw Reader’s attention to the issue of impact of separate measurement of features (attributes) from which we want to make inferences. It turns out, that the fact of separate measurements implies algorithmic simplifications for many forms of reasoning in DST. Basic theorems and algorithms exploiting this are given.
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Symbolic Dempster-Shafer Theory
Journal of Computer Research and Development, 2005采用一个全序的符号值集合来代替数值信任度集合[0,1],提出定性Dempster-Shfer理论来处理既有不确定性又有不精确性的推理问题.首先,定义了适合对不确定性进行定性表达和推理的定性mass函数、定性信任函数等概念,并且研究了这些概念之间的基本关系;其次,详细讨论了定性证据合成问题,提出了基于平均策略的证据合成规则.这种定性Dempster-Shfer理论与其他相关理论相比,既通过在定性领域重新定义Dempster-Shfer理论的基本概念,继承了Dempster-Shfer理论在不确定推理方面的主要特点,同时又具有适合对不精确性操作的既有严格定义又符合直观特性的定性算子,因此更适合基于Dempster-Shafer理论框架不精确表示和处理不确定性.
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A novel combination methodology for Dempster-Shafer theory
2017 25th Signal Processing and Communications Applications Conference (SIU), 2017In this study, a new methodology for combining probability masses from different sources is proposed for Dempster-Shafer theory. Unlike the existing works in the literature, this methodology treats the combination problem as an optimization problem and proposes an objective function that uses conflict and entropy measures to solve this problem.
Hasan Ihsan Turhan, Mübeccel Demirekler
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On the fuzzy generalization of the Dempster-Shafer theory of evidence
2010 International Conference on Machine Learning and Cybernetics, 2010In this paper we develop the fuzzy generalization of the Dempster-Shafer theory of evidence. Two pairs of fuzzy valued belief and plausibility functions are constructed by a fuzzy T-similarity relation. These functions take values in the fuzzy unit interval, a well known concept in fuzzy topology theory.
Eric C. C. Tsang, Degang Chen 0002
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Categorification of the Dempster Shafer theory
SPIE Proceedings, 2015This paper contains preliminary steps in demonstrating how the Dempster Shafer theory can be placed into the framework of category theory. In the Dempster Shafer setting, the elements of the base set of a probability space are, typically, subsets of some set.
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Dempster-Shafer Theory in Recommender Systems: A Survey
International Journal of Uncertainty, Fuzziness and Knowledge-Based SystemsDue to the limitations associated with the use of a single type of data during the recommendation process, recent research has focused on developing new fusion-based recommenders that make use of multiple heterogeneous sources of information to provide more accurate suggestions.
Khadidja Belmessous +4 more
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Some convergence results in Dempster-Shafer theory
Soft Computing - A Fusion of Foundations, Methodologies and Applications, 2002Belief functions and basic probability assignments defined on a finite frame of discernment are given an intuitive extension. Some convergence results are then given on sets converging from above and below; also, a weakened form of one of the Borel-Cantelli lemmas is given. The paper concludes with a theorem on the Dempster-Shafer random variable.
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Dempster-Shafer Evidential Theory
2009Dempster-Shafer evidential theory, a probability-based data fusion classification algorithm, is useful when the sensors (or more generally, the information sources) contributing information cannot associate a 100 percent probability of certainty to their output decisions.
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Dempster-Shafer and Possibility Theory
2016The last chapter presents an application of a particular class of normalized capacities (belief and plausibility measures) to the representation of uncertainty. This class has very specific properties and can be obtained through very different approaches (upper and lower probabilities, evidence theory and random sets, at least).
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