As is well known, Dempster-Shafer theory offers an alternative approach to deal with uncertainty reasoning in expert systems and other fields. In this paper, we present two results that relate to the use of the theory. First, we present and analyze four methods to induce uncerioin rules fvlm a training instance set for Dempster-Shafer theory. This is the first attempt to do so, to the best of o...

World Health Organization reports that African Trypanosomiasis affects mostly poor populations living in remote rural areas of Africa that can be fatal if properly not treated. This paper presents Dempster-Shafer Theory for the detection of African trypanosomiasis. Sustainable elimination of African trypanosomiasis as a public-health problem is feasible and requires continuous efforts and innov...

In social media, trust and distrust among users are important factors in helping users make decisions, dissect information, and receive recommendations. However, the sparsity and imbalance of social relations bring great difficulties and challenges in predicting trust and distrust. Meanwhile, there are numerous inducing factors to determine trust and distrust relations. The relationship among i...

The latest developments in Markov models’ theory and their corresponding computational techniques have opened new rooms for image and signal modeling. In particular, the use of Dempster–Shafer theory of evidence within Markov models has brought some keys to several challenging difficulties that the conventional hidden Markov models cannot handle. These difficulties are concerned mainly with two...

This paper examines the relationship between Shafer's belief functions and convex sets of probability distributions. Kyburg's (1986) result showed that belief function models form a subset of the class of closed convex probability distributions. This paper emphasizes the importance of Kyburg's result by looking at simple examples involving Bernoulli trials. Furthermore, it is shown that many co...

A sufficient condition is developed for the equality of the plausibility and commonality measures of the Dempster-Shafer belief calculus. When the condition is met, as it is in many applications, an efficient method to calculate relative plausibility is available. In particular, the method can be used to calculate the relative plausibility of atomic hypotheses and, therefore, it can be used to ...

The Dempster-Shafer “theory of evidence” encompasses and extends the Bayes Theorem-based decision making machinery. Dempster-Shafer’s innovation is the introduction of lower and upper bounds, designated “belief” and “plausibility”, that are attached to probability estimates. The Dempster-Shafer algebra provides for propagation of and reasoning about these quantities according to an algebra whos...

This paper presents a supervised classi®cation model integrating fuzzy reasoning and Dempster±Shafer propagation of evidence has been built on top of connectionist techniques to address classi®cation tasks in which vagueness and ambiguity coexist. The salient aspect of the approach is the integration within a neuro-fuzzy system of knowledge structures and inferences for evidential reasoning bas...

Cognitive radio (CR) is a promising technology that brings about remarkable improvement in spectrum utilization. To tackle the hidden terminal problem, cooperative spectrum sensing (CSS) which benefits from the spatial diversity has been studied extensively. Since CSS is vulnerable to the attacks initiated by malicious secondary users (SUs), several secure CSS schemes based on Dempster-Shafer t...

In the current versions of the Dempster-Shafer theory, the only essential restriction on the validity of the rule of combination is that the sources of evidence must be statistically independent. Under this assumption, it is permissible to apply the Dempster-Shafer . rule to two or more distinct probability distributions. An essential step in the Dempster-Shafer rule of combination of evidence ...