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 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...

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

This paper presents a supervised classi®cation model integrating fuzzy reasoning and Dempster±Shafer propagation of evidence has been built on top of connectionist techniques to address classi®cation tasks in which vagueness and ambiguity coexist. The salient aspect of the approach is the integration within a neuro-fuzzy system of knowledge structures and inferences for evidential reasoning bas...

This paper presents a general framework for the study of rough fuzzy sets in which fuzzy sets are approximated in a crisp approximation space. By the constructive approach, a pair of lower and upper generalized rough fuzzy approximation operators is first defined. The rough fuzzy approximation operators are represented by a class of generalized crisp approximation operators. Properties of rough...

Dempster-Shafer evidence theory has been extensively used in many information fusion systems since it was proposed by Dempster and extended by Shafer. Many scholars have been conducted on conflict management of Dempster-Shafer evidence theory in past decades. However, how to determine a potent parameter to measure evidence conflict, when the given environment is in an open world, namely the fra...

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...

We introduce a general theory of epistemic random fuzzy sets for reasoning with or crisp evidence. This framework generalizes both the Dempster-Shafer belief functions, and possibility theory. Independent are combined by generalized product-intersection rule, which extends Dempster's rule combining product conjunctive combination distributions. Gaussian numbers their multi-dimensional extension...

introduction environmental impact assessment is a systematic process to identify, predict and evaluate the environmental effects of proposed actions and projects. this process is applied prior to major decisions and commitments being made. environment, social, cultural and health effects are considered as an integral part of eia. particular attention is paid to eia practice for preventing, miti...