Dempster-Shafer evidence theory (D-S) is an effective instrument for merging the collected pieces of basic probability assignment (BPA), and it exhibits superiority in achieving robustness soft computing decision making uncertain imprecise environment. However, determination BPA still uncertain, merely applying can sometimes lead to counterintuitive results when lines conflict. In this paper, a...

The Dempster-Shafer theory of belief functions is an important approach to deal with uncertainty in AI. In the theory, belief functions are defined on Boolean algebras of events. In many applications of belief functions in real world problems, however, the objects that we manipulate is no more a Boolean algebra but a distributive lattice. In this paper, we extend the Dempster-Shafer theory to t...

The conditioning in the Dempster-Shafer Theory of Evidence has been defined (by Shafer [15] as combination of a belief function and of an ”event” via Dempster rule. On the other hand Shafer [15] gives a ”probabilistic” interpretation of a belief function (hence indirectly its derivation from a sample). Given the fact that conditional probability distribution of a sample-derived probability dist...

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 clinical diagnosis support system which combines the advantages of Dempster-Shafer theory with Bayesian networks in order to simulate the uncertain medical reasoning. We propose a hierarchical structure using Dempster-Shafer at the upper level for evaluating more general hypothesis (disease groups) and Bayesian networks at the lower level for a more accurate analysis of sp...

Data fusion technology can be the best way to extract useful information from multiple sources of data. It has been widely applied in various applications. This paper presents a data fusion approach in multimedia data for event detection in twitter by using Dempster-Shafer evidence theory. The methodology applies a mining algorithm to detect the event. There are two types of data in the fusion....