The Dempster-Shafer theory of evidence accumulation is one of the main tools for combining data obtained from multiple sources. In this paper a special case of combination of two bodies of evidence with non-zero conflict coefficient is considered. It is shown that application of the Dempster-Shafer rule of combination in this case leads to an evaluation of masses of the combined bodies that is ...

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...

Dempster–Shafer evidence theory has been widely used in various fields of applications. Besides, it has been proven that the quantum theory has powerful capabilities of solving the decision making problems. However, due to the inconsistency of the expression, the classical Dempster–Shafer evidence theory modelled by real numbers can not be integrated directly with the quantum theory modelled by...

The purpose of this chapter is to demonstrate the use of evidential reasoning approach under Dempster-Shafer (D-S) theory of belief functions to analyze revealed causal maps. Revealed causal mapping (RCM) technique, as applied in this chapter, is a qualitative method used to develop or extend understanding of a phenomenon within a specific context. The map can be used to develop models, either ...

An approach to fuse multiple images based on Dempster-Shafer evidential reasoning is proposed in this article. Dempster-Shafer theory provides a complete framework for combining weak evidences from multiple sources. Such situations typically arise in the image fusion problems, where a ‘real scene’ image has to be estimated from incomplete and unreliable observations. By converting images from t...

It is critical to build an effective prediction model to improve the accuracy of financial distress prediction. Some existing literatures have demonstrated that single classifier has limitations and combination of multiple prediction methods has advantages in financial distress prediction. In this paper, we extend the research of multiple predictions to integrate with rough set and Dempster–Sha...

as the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. this processing comprises two fundamental and critical steps towar...

Detection of brain tissues using magnetic resonance imaging (MRI) is an active and challenging research area in computational neuroscience. Brain MRI artifacts lead to an uncertainty in pixel values. Therefore, brain MRI segmentation is a complicated concern which is tackled by a novel data fusion approach. The proposed algorithm has two main steps. In the first step the brain MRI is divided to...

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...