This paper introduces the idea of using the Dempster-Shafer theory of evidence with qualitative values. Dempster-Shafer theory is a formalism for reasoning under uncertainty which may be viewed as a generalisation of probability theory with special advantages in its treatment of ambiguous data and the ignorance arising from it. Here we are interested in applying the theory when the numbers that...

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...

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...

This paper aims at bridging together the fields of Uncertain Reasoning and Knowledge Representation. The bridge we propose consists in the definition of a Hybrid Belief System, a general modular system capable of performing uncertain reasoning on structured knowledge. This system comprises two distinct modules, UR-mod and KR-mod: the UR-mod provides the uncertainty calculus used to represent un...

This paper has dealt with a data fusion for the problem of land-cover classification using multisensor imagery. Dempster-Shafer evidence theory has been employed to combine the information extracted from the multiple data of same site. The Dempster-Shafer’s approach has two important advantages for remote sensing application: one is that it enables to consider a compound class which consists of...

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 ...