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Assessing system reliability and allocating resources: a bayesian approach that integrates multi-level data

Journal Article · · Journal of Quality Technology
OSTI ID:960611
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)
Sponsoring Organization:
DOE
DOE Contract Number:
AC52-06NA25396
OSTI ID:
960611
Report Number(s):
LA-UR-08-05484; LA-UR-08-5484
Journal Information:
Journal of Quality Technology, Journal Name: Journal of Quality Technology
Country of Publication:
United States
Language:
English

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