@inproceedings{aac591977e064caf8eb3ec796e01db83,
title = "Bayesian network modeling of system performance",
abstract = "Bayesian Networks (BNs) provide an excellent framework for modeling system performance, particularly in near-real time applications when it is necessary to update models in light of observations. However, BNs can be very demanding of computer memory and inference can become intractable if care is not taken to optimize their topology. In this paper, efficient BN formulations for modeling system performance are presented. First, formulations are developed for series and parallel systems. Then, results are extended to general systems for which the minimal link and/or cut sets are known. Finally, an optimization algorithm is developed to automate the generation of efficient BN formulations for modeling system performance.",
author = "Bensi, {M. T.} and {Der Kiureghian}, A. and D. Straub",
year = "2010",
doi = "10.1201/b10497-2",
language = "English",
isbn = "9780415881791",
series = "Reliability and Optimization of Structural Systems - Proceedings of Reliability and Optimization of Structural Systems",
publisher = "Association for Computing Machinery",
pages = "1--8",
booktitle = "Reliability and Optimization of Structural Systems - Proceedings of Reliability and Optimization of Structural Systems",
note = "15th International Federation of Information Processing (IFIP) Working Group 7.5 on Reliability and Optimization of Structural Systems ; Conference date: 07-04-2010 Through 10-04-2010",
}