The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inference and is increasingly used in the field of reliability evaluation. This paper presents a bibliographic review of BNs that have been proposed for reliability evaluation in the last decades. Studies are classified from the perspective of the objects of reliability evaluation, i.e., hardware, structures, software, and humans. For each classification, the construction and validation of a BN-based reliability model are emphasized. The general procedural steps for BN-based reliability evaluation, including BN structure modeling, BN parameter modeling, BN inference, and model verification and validation, are investigated. Current gaps and challenge...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modelling many kinds of...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
Success Likelihood Index Model (SLIM) is one of the widely-used deterministic techniques in human re...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...