Assessing system reliability and allocating resources: a bayesian approach that integrates multi-level data
Journal Article
·
· Journal of Quality Technology
OSTI ID:960611
- Los Alamos National Laboratory
Good estimates of the reliability of a system make use of test data and expert knowledge at all available levels. Furthermore, by integrating all these information sources, one can determine how best to allocate scarce testing resources to reduce uncertainty. Both of these goals are facilitated by modern Bayesian computational methods. We apply these tools to examples that were previously solvable only through the use of ingenious approximations, and use genetic algorithms to guide resource allocation.
- Research Organization:
- Los Alamos National Laboratory (LANL), Los Alamos, NM (United States)
- Sponsoring Organization:
- USDOE
- DOE Contract Number:
- AC52-06NA25396
- OSTI ID:
- 960611
- Report Number(s):
- LA-UR-08-05484; LA-UR-08-5484; TRN: US201006%%1251
- Journal Information:
- Journal of Quality Technology, Journal Name: Journal of Quality Technology
- Country of Publication:
- United States
- Language:
- English
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