We develop a new approach for decision making with Dempster-Shafer theory of evidence by using uncertain information represented in the form of interval numbers. We suggest the use of different types of uncertain aggregation operators in the problem. Then, we obtain new aggregation operators such as the belief structure uncertain ordered weighted averaging (BSUOWA) operator and the BS uncertain...

In this pa�, we suggest marry ing Dempster-Shafer (DS) theory w1th Knowledge Representation (KR). Born out of this marr iage is the defmition of "Dempster-Shafer Belief Bases", abstract data types representing uncertain knowledge that use DS theory for representing strength of belief about our knowledge, and the linguistic structures of an arbitrary KR system for representing the knowledge itse...

This paper is one of many attempts to introduce graphical Markov models within Dempster-Shafer theory of evidence. Here we take full advantage of the notion of factorization, which in probability theory (almost) coincides with the notion of conditional independence. In Dempster-Shafer theory this notion can be quite easily introduced with the help of the operator of composition. Nevertheless, t...

Evidentia.l rea.. '>oning in ex pert systems has often used ad-hoc uncertainty calculi. Although it is generally accepted that probability theory provides a firm theoretical fo undat ion, researchers have found some problems with its usc as a workable uncertainty calculus. Among these problems arc representation ol' ignorance, consistency of probabilistic judgements, and adjustment of a priori ...

We discuss the role of fuzzy sets in modeling business rules. The technology involved in fuzzy systems modeling is described. We next introduce some ideas from the Dempster-Shafer theory of evidence. We use the Dempster-Shafer framework to provide a machinery for including randomness in the fuzzy systems

Today due to the importance and necessity of implementing security systems in homes and other buildings, systems with higher certainty, lower cost and with sensor fusion methods are more attractive, as an applicable and high performance methods for the researchers. In this paper, the application of Dempster-Shafer evidential theory and also the newer, more general one Dezert-Smarandache theory ...

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...

In this paper, target differentiation based on pattern of data which are obtained by a set of two ultrasonic sensors is considered. A neural network based target classifier is applied to these data to categorize the data of each sensor. Then the results are fused together by Dempster–Shafer theory (DST) and Dezert–Smarandache theory (DSmT) to make final decision. The Generalized Aggregated Unce...