The origins of Dempster-Shafer theory (DST) go back to the work by Dempster (1967) who developed a system of upper and lower probabilities. Following this, his student Shafer (1976), in his book “A Mathematical Theory of Evidence” added to Dempster’s work, including a more thorough explanation of belief functions. In summary, it is a methodology for evidential reasoning, manipulating uncertaint...

The Dempster-Shafter Theory is well-known for its usefulness to express uncertain judgments of experts. This contribution shows how to apply the calculus to safety and reliability modelling, especially to expert judgement; Failure Modes, Effects, and Criticality Analysis; Event Tree Analysis, Fault Tree Analysis, and Reliability Centred Maintenance. Including a tutorial introduction to the Demp...

This chapter presents a general overview and foundations of the DSmT, i.e. the recent theory of plausible and paradoxical reasoning developed by the authors, specially for the static or dynamic fusion of information arising from several independent but potentially highly conflicting, uncertain and imprecise sources of evidence. We introduce and justify here the basis of the DSmT framework with ...

Efficient modeling of uncertain information in real world is still an open issue. Dempster-Shafer evidence theory is one of the most commonly used methods. However, the Dempster-Shafer evidence theory has the assumption that the hypothesis in the framework of discernment is exclusive of each other. This condition can be violated in real applications, especially in linguistic decision making sin...

This paper proposes a novel approach to case-based decision analysis supported by case-based reasoning (CBR). The strength of CBR is utilized for building a situation dependent decision model without complete domain knowledge. This is achieved by deriving states probabilities and general utility estimates from the case library and the subset of cases retrieved in a situation described in query....

This paper describes an ensemble design for cyber security threats detection, which fuses the results from multiple classifiers together to make a final assessment decision. For promoting both speed and accuracy in the detection performance, only some of the features in traffic data are selected for each base classifier. In the kernel of each classifier, we combine Dempster-Shafer theory with k...

We present a model for representing relevance and classification decisions of multiple catalogers in the context of a hierarchical bibliographical database. The model is based on the Dempster-Shafer theory of evidence. Concepts like ambiguous relevance, inexact classification, and pooled classification, are discussed using the nomenclature of belief functions and Dempster's rule. The model thus...

Traditional Dempster Shafer belief theory does not provide a simple method for judging the effect of statistical and probabilistic data on belief functions and vice versa. This puts belief theory in isolation from probability theory and hinders fertile cross-disciplinary developments, both from a theoretic and an application point of view. It can be shown that a bijective mapping exists between...