We present a Dempster-Shafer (DS) approach to finding confidence bounds on the mass of the Higgs boson. Dempster-Shafer is a statistical framework that generalizes Bayesian statistics. DS calculus augments traditional probability by allowing mass to be distributed over power sets of the event space. This eliminates the Bayesian dependence on prior distributions while allowing the incorporation ...

Given a number of Dempster-Shafer belief functions there are different architectures which allow to do a compilation of the given knowledge. These architectures are the Shenoy-Shafer Architecture, the Lauritzen-Spiegelhalter Architecture and the HUGIN Architecture. We propose a new architecture called ”Fast-Division Architecture” which is similar to the former two. But there are two important a...

In this paper we develop methods for selection of templates and use these templates to recluster an already performed Dempster-Shafer clustering taking into account intelligence to template fit during the reclustering phase. By this process the risk of erroneous force aggregation based on some misplace pieces of evidence from the first clustering process is greatly reduced. Finally, a more reli...

The objective of this paper is to describe the potential o€ered by the Dempster±Shafer theory (DST) of evidence as a promising improvement on ``traditional'' approaches to decision analysis. Dempster±Shafer techniques originated in the work of Dempster on the use of probabilities with upper and lower bounds. They have subsequently been popularised in the literature on Arti®cial Intelligence (AI...

We formulate Dempster Shafer Belief functions in terms of Propositional Logic, using the im­ plicit notion of provability underlying Demp­ ster Shafer Theory. The assignment of weights to the propositional literals enables the Belief functions to be explicitly computed using Net­ work Reliability techniques. Also, the updat­ ing of Belief functions using Dempster's Rule of Combination correspon...

Dempster-Shafer evidence theory is an efficient method to process uncertain, incomplete and vague information in data fusion. The combination of conflicting bodies of evidence has been one of the most important issues in Dempster-Shafer evidence theory since the example of counter-intuitive results produced by Dempster’s rule was found. Based on the framework of the Dempster-Shafer evidence the...

This paper develops a new uncertainty measure for the theory of hints that complies with the established semantics of statistical information theory and further satisfies all classical requirements for such a measure imposed in the literature. The proposed functional decomposes into conversant uncertainty measures and therefore discloses a new interpretation of the latters as well. By abstracti...

This paper presents a novel map building approach for path planning purposes, which takes into account the uncertainty inherent in sensor measurements. To this end, Bayesian estimation and Dempster-Shafer evidential theory are used to fuse the sensory information and to update the occupancy and evidential grid maps, respectively. The approach is illustrated using actual measurements from a labo...

Software Quality and Reliability Prediction Using Dempster-Shafer Theory

ARIOUS structural and physiological barriers to recombination in species Vhyb rids often impose rigorous limitations upon the extent to which the characters of one species may be combined with those of another. Among such barriers structural and genic imbalance resulting in the differential elimination of gametes and zygotes of recombination types has often been mentioned (ANDERSON 1939; DEMPST...