IPMU 2012: Advances in Computational Intelligence pp 481-490 | Cite as
Dynamic Directed Evidential Networks with Conditional Belief Functions: Application to System Reliability
Conference paper
Abstract
The temporal dimension is a very important aspect which must be taken into consideration when reasoning under uncertainty.
The main purpose of this paper is to address this problem by a new evidential framework for modeling temporal changes in data. This method, allowing to model uncertainty and to manage time varying information thanks to the evidence theory, offers an alternative framework for dynamic probabilistic and dynamic possibilistic networks. It is applied to a system reliability analysis for the sake of illustration.
Keywords
Dynamic graphical models theory of evidence time varying information managing uncertaintyPreview
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