YesBayesian Network (BN)-based methods are increasingly used in system reliability analysis. While BNs enable to perform multiple analyses based on a single model, the construction of robust BN models relies either on the conversion from other intermediate system model structures or direct analyst-led development based on experts input, both requiring significant human effort. This article proposes an architecture model-based approach for the direct generation of a BN model. Given the architectural model of a system, a systematic bottom-up approach is suggested, underpinned by failure behaviour models of components composed based on interaction models to create a system-level failure behaviour model. Interoperability and reusabili...
We present a continuous-time Bayesian network (CTBN) framework for dynamic systems reliability model...
Hazardous events in process plants like the leakage of dangerous substances can result in severe dam...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
This paper proposes a methodology to apply Bayesian networks to structural system reliability reasse...
AbstractIn this paper, we present an approach to reliability modeling and analysis based on the auto...
A class of functional model known as multilevel flow model (MFM) is used to represent a pilot scale ...
In this paper, we present an approach to reliability modeling and analysis based on the automatic c...
Traditional reliability models, such as fault tree analysis (FTA) and reliability block diagram (RBD...
In this paper, a model for failure analysis using the theory of Bayesian Belief Networks (BBN), will...
In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relation...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Due to the nature of software faults and the way they cause system failures new methods are needed f...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Bayesian Networks (BN) have in previous literature been recognized as a powerful tool for safety ana...
We present a continuous-time Bayesian network (CTBN) framework for dynamic systems reliability model...
Hazardous events in process plants like the leakage of dangerous substances can result in severe dam...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
This paper proposes a methodology to apply Bayesian networks to structural system reliability reasse...
AbstractIn this paper, we present an approach to reliability modeling and analysis based on the auto...
A class of functional model known as multilevel flow model (MFM) is used to represent a pilot scale ...
In this paper, we present an approach to reliability modeling and analysis based on the automatic c...
Traditional reliability models, such as fault tree analysis (FTA) and reliability block diagram (RBD...
In this paper, a model for failure analysis using the theory of Bayesian Belief Networks (BBN), will...
In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relation...
The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inferen...
Due to the nature of software faults and the way they cause system failures new methods are needed f...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
Bayesian Networks (BN) have in previous literature been recognized as a powerful tool for safety ana...
We present a continuous-time Bayesian network (CTBN) framework for dynamic systems reliability model...
Hazardous events in process plants like the leakage of dangerous substances can result in severe dam...
The objective of this paper is to present work on how a Bayesian Belief Network for a software safet...