This paper presents an efficient adaptation and application of the Dempster-Shafer theory of evidence, one that can be used effectively in a massively parallel hierarchical system for visual pattern perception. It describes the techniques used, and shows in an extended example how they serve to improve the system's performance as it applies a multiple-level set of processes.

We survey three applications of mathematical programming to rea soning under uncertainty a an application of linear programming to probabilistic logic b an application of nonlinear programming to Bayesian logic a combination of Bayesian inference with probabilistic logic and c an application of integer programming to Dempster Shafer theory which is a method of combining evidence from di erent s...

John Yen l;sc 1 Information Sciences Institute 46i6 Admiralty Way l\Iarina del Rey. CA. 90292 Dempster's rule of combination has been the most controversial part of the Dempster-Shafer (D-S) theory. In particular, Zadeh has reached a conjecture on the noncombinability of evidence from a relational model of the D-S theory. In this paper. we will describe another relational model where D-S masses...

Dempster-Shafer evidence theory is a powerful tool in information fusion. When the evidence are highly conflicting, the counter-intuitive results will be presented. To adress this open issue, a new method based on evidence distance of Jousselme and Hausdorff distance is proposed. Weight of each evidence can be computed, preprocess the original evidence to generate a new evidence. The Dempster’s...

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...

The aim of this paper is to show that Dempster–Shafer evidence theory may be successfully applied to unsupervised classification in multisource remote sensing. Dempster–Shafer formulation allows to consider unions of classes, and to represent both imprecision and uncertainty, through the definition of belief and plausibility functions. These two functions, derived from mass function, are genera...

this study represents an intelligence procedure for diagnosis simultaneously avian newcastle disease virus, infection bronchitis virus and influenza using heart sound signal. for this aim, the chickens were divided into four groups. the first group was considered as control samples. the second, third and fourth groups were infected with newcastle disease virus, infection bronchitis and avian in...

The integration of different kinds of remotely sensed data, in particular Synthetic Aperture Radar (SAR) and optical satellite imagery, is considered a promising approach for land cover classification because of the complimentary properties of each data source. However, the challenges are: how to fully exploit the capabilities of these multiple data sources, which combined datasets should be us...