Even though various frameworks exist for reasoning under uncertainty, a realistic fault
diagnosis task does not fit into any of them in a straightforward way. For each framework …

Expressions and propagations of uncertainties have been the core topics in the
development of risk science in last decades, whose purpose is to provide decision-makers …

Inference algorithms in directed evidential networks (DEVN) obtain their efficiency by
making use of the represented independencies between variables in the model. This can be …

Modern training through virtual environments is widely used in transport in order to provide a
high level of precision and more and more complex situations. These virtual environments …

After it has been successfully done in probability and possibility theories, the paper is the
first attempt to introduce the operator of composition also for belief functions. We prove that …

End-of-life management of complex systems is increasingly important for industry because
of growing environmental concerns and associated regulations. In many areas, lack of …

Abstract The Transferable Belief Model (TBM) relies on belief functions and enables one to
represent and combine a variety of knowledge from certain up to ignorance as well as …

Cette thèse porte sur la problématique de reconnaissance automatique de systèmes
dynamiques. Une méthodologie basée sur des modèles de séquences d'états est …

The prioritization of capability gaps for weapon system of systems is the basis for design and
capability planning in the system of systems development process. In order to address input …

In the context of human action sequence recognition in video sequences, a scheduler of
actions is proposed. The belief scheduler is based on a temporal belief filter ensuring a …