@article {5633,
	title = {Bayesian Networks for Frequency Analysis in Dependability},
	journal = {J Fail. Anal. and Preven},
	volume = {2018},
	number = {18},
	year = {2018},
	pages = {538{\textendash}544},
	abstract = {The high suppleness of Bayesian networks has led to their wide application in a variety of dependability modeling and analysis problems. The main objective of this paper is to extend the use of such powerful tool to estimate the occurrence frequency of failures and consequences in a straightforward way. Such extension is based on the employment of a transformation operator to substitute the original terms with matrices that hold the full dependability description of the corresponding element. Two simple case studies in reliability and safety contexts are treated using the suggested method whose results are validated through their comparison to the corresponding results of other classical dependability techniques.},
	url = {HTTP://doi.org/10.1007/s11668-018-0433-5},
	author = {MCHEBILA}
}
