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Propagation of Belief Functions in Singly-Connected Hybrid Directed Evidential Networks

  • Wafa LaâmariEmail author
  • Boutheina Ben Yaghlane
Conference paper
  • 394 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9310)

Abstract

Directed evidential networks (DEVNs) can be seen, at present, as an extremely powerful graphical tool for representing and reasoning with uncertain knowledge in the framework of evidence theory.

The main purpose of this paper is twofold. Firstly, it introduces hybrid directed evidential networks which generalize the standard DEVNs. Secondly, it presents an algorithm for performing inference over singly-connected hybrid evidential networks.

Keywords

Evidence Network Conditional Belief Functions Conditionals Specified Generalized Bayesian Theorem (GBT) Child Nodes 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.LARODEC Laboratory - Institut Supérieur de Gestion de TunisTunisTunisia

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