In this paper, a new Fuzzy Morphology (FM) based on the GeneralizedDempster-Shafer Theory (GDST) is proposed. At first, in order to clarify the similarity ofdefinitions between Mathematical Morphology (MM) and Dempster-Shafer Theory (DST),dilation and erosion morphological operations are studied from a different viewpoint. Then,based on this similarity, a FM based on the GDST is proposed. Unlik...

Dempster-Shafer theory is widely applied to uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. However, some conditions, such as exclusiveness hypothesis and completeness constraint, limit its development and application to a large extend. To overcome these shortcomings in Dempster-Shafer theory and enhance its capability of representing uncert...

Stochastic Multicriteria Acceptability Analysis (SMAA) is a family of methods to aid decision makers (DMs) in discrete decision making problems. SMAA methods are capable of handling preference information of various types. The imprecise preferences of multiple DMs can for example be represented by a joint probability distribution for criteria weights. Dempster-Shafer theory with Analytic Hierar...

The goal of this paper is to study the connection between Dempster-Shafer theory and probabilistic argumentation systems. By introducing a general method to translate probabilistic argumentation systems into corresponding Dempster-Shafer belief potentials, its contribution is twofold. On the one hand, the paper proposes probabilistic argumentation systems as a convenient and powerful modeling l...

Mathematical models are frequently developed to try to predict whether an individual has one of several conditions given a number of measured factors. Frequently, multiple models are developed for the same sets of data and, in general, some work better than others and usually one is selected as the primary model. But is there some way to use multiple models to aid prediction? In earlier work, w...

Dempster-Shafer evidence theory is widely used in the fields of decision level information fusion. In order to overcome the problem of the counter-intuitive results encountered when using Dempster’s combination rule to combine the evidences which exist high conflict, a modified sequential weighted evidence combination is proposed. Firstly, the credibility of each evidence can be obtained based ...

Dempster-Shafer theory offers an alternative to traditional probabilistic theory for the mathematical representation of uncertainty. The significant innovation of this framework is that it allows for the allocation of a probability mass to sets or intervals. DempsterShafer theory does not require an assumption regarding the probability of the individual constituents of the set or interval. This...

The spatial prediction of land cover at the field scale in winter appears useful for the issue of bare soils reduction in agricultural intensive regions. High variability of the factors that motivate the land cover changes between each winter involves integration of uncertainty in the modelling process. Fusion process with Dempster-Shafer Theory (DST) presents some limits in generating errors i...

Dempster-Shafer theory is widely applied in uncertainty modelling and knowledge reasoning due to its ability of expressing uncertain information. A distance between two basic probability assignments(BPAs) presents a measure of performance for identification algorithms based on the evidential theory of Dempster-Shafer. However, some conditions lead to limitations in practical application for Dem...