2009
DOI: 10.1016/j.jspi.2008.05.042
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Using Bayesian Networks in reliability evaluation for an -out-of-:F distributed communication system

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Cited by 11 publications
(7 citation statements)
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“…The properties of the modeling framework that make BNs particularly well suited for reliability applications are discussed [2]. Honari et al [3] developed a new approach using BN to evaluate the reliability of an (r,s)-out-of-(m,n): F system. Norrington et al [4] used a BN method to model the reliability of search and rescue operations within UK Coastguard coordination centers.…”
Section: Introductionmentioning
confidence: 99%
“…The properties of the modeling framework that make BNs particularly well suited for reliability applications are discussed [2]. Honari et al [3] developed a new approach using BN to evaluate the reliability of an (r,s)-out-of-(m,n): F system. Norrington et al [4] used a BN method to model the reliability of search and rescue operations within UK Coastguard coordination centers.…”
Section: Introductionmentioning
confidence: 99%
“…Dynamic BNs (DBNs), which are longestablished extensions of ordinary BNs and allow explicit modeling of changes over time, were developed subsequently. In recent years, BNs and DBNs have been applied to study the reliability of multilevel systems [14], two-terminal networks [15], distributed communication systems [16], N-modular redundant systems [17], structural systems [18], human factors [19], and software systems [20]. BNs and DBNs have also been used to study the fault diagnosis of computer numerical control machine tools [21], chillers [22], and ground-source heat pumps [23].…”
Section: Introductionmentioning
confidence: 99%
“…The failures of hardware or software significantly affect the operated systems, and these failures have been widely investigated to evaluate system reliability. The reliability of PLC‐based hot standby systems and N‐modular redundant computer systems has been evaluated using Markov models, Bayesian network models, or a combination of both . In addition, the reliability of software systems has been studied using Markov and Bayesian network models …”
Section: Introductionmentioning
confidence: 99%