Name
Title | ||
|---|---|---|
Bayesian Networks Implementation of the Dempster Shafer Theory to Model Reliability Uncertainty |
Abstract | ||
|---|---|---|
In many reliability studies based on data, reliability engineers face incompleteness and incoherency problems in the data. Probabilistic tools badly handle these kinds of problems thus, it is better to use formalism from the evidence theory. From our knowledge, there is a lack of industrial tools that implement this theory. In this paper, the implementation of the Dempster Shafer theory in a Bayesian Network tool is proposed in order to compute system reliability and manage epistemic uncertainty propagation. The basic concepts used are presented and some numerical experiments are made to show how uncertainty is propagated. |
Year | DOI | Venue |
|---|---|---|
2006 | 10.1109/ARES.2006.38 | ARES |
Keywords | Field | DocType |
dempster shafer theory,incoherency problem,industrial tool,system reliability,reliability study,evidence theory,basic concept,epistemic uncertainty propagation,bayesian networks implementation,model reliability uncertainty,reliability engineer,bayesian network tool,probability,bayesian network,epistemic uncertainty,bayesian methods,reliability theory,data engineering,uncertainty,case based reasoning,computer networks,reliability engineering,nonmonotonic reasoning | Data mining,Uncertainty quantification,Computer science,Bayesian network,Artificial intelligence,Non-monotonic logic,Probabilistic logic,Formalism (philosophy),Case-based reasoning,Dempster–Shafer theory,Machine learning,Reliability theory | Conference |
ISBN | Citations | PageRank |
0-7695-2567-9 | 4 | 0.50 |
References | Authors | |
9 | 2 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Christophe Simon | 1 | 162 | 14.35 |
| Philippe Weber | 2 | 44 | 3.49 |