Add to ORKGOver the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of statistical problems. In this chapter we will discuss the properties of the modeling framework that make BNs particularly well suited for reliability applications. This discussion is closely linked to the analysis of a real-world example
This paper proposes a methodology to apply Bayesian networks to structural system reliability reasse...
In this paper, we present an approach to reliability modeling and analysis based on the automatic c...
A Bayesian network (BN) is a powerful tool to represent the quantitative and qualitative features 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 modelling many kinds of...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
This paper considers the problem of reliability analysis of that consists groups of components organ...
Bayesian networks (BN) have recently experienced increased interest and diverse applications in nume...
We present a continuous-time Bayesian network (CTBN) framework for dynamic systems reliability model...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
This paper proposes a methodology to apply Bayesian networks to structural system reliability reasse...
In this paper, we present an approach to reliability modeling and analysis based on the automatic c...
A Bayesian network (BN) is a powerful tool to represent the quantitative and qualitative features 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 modelling many kinds of...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
This paper considers the problem of reliability analysis of that consists groups of components organ...
Bayesian networks (BN) have recently experienced increased interest and diverse applications in nume...
We present a continuous-time Bayesian network (CTBN) framework for dynamic systems reliability model...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Bayesian networks are a very general and powerful tool that can be used for a large number of proble...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
This paper proposes a methodology to apply Bayesian networks to structural system reliability reasse...
In this paper, we present an approach to reliability modeling and analysis based on the automatic c...
A Bayesian network (BN) is a powerful tool to represent the quantitative and qualitative features of...