Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
806540 | Reliability Engineering & System Safety | 2007 | 8 Pages |
Abstract
Bayesian networks have recently found many applications in systems reliability; however, the focus has been on binary outcomes. In this paper we extend their use to multilevel discrete data and discuss how to make joint inference about all of the nodes in the network. These methods are applicable when system structures are too complex to be represented by fault trees. The methods are illustrated through four examples that are structured to clarify the scope of the problem.
Related Topics
Physical Sciences and Engineering
Engineering
Mechanical Engineering
Authors
Alyson G. Wilson, Aparna V. Huzurbazar,