Abstract: In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relationship between system failure and component failure can be expressed by probability importance degree, structure importance degree and key importance degree in FTA (Fault Tree Analysis). BN supplies a new method to reflect the importance of components in system. That is the conditional failure probability which points out the most possible reason of system failure and is more reasonable and reliable. Some examples are given to allocate the reliability of systems by BN and the results show that BN is useful and effective
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relation...
abstract: Bayesian networks are powerful tools in system reliability assessment due to their flexibi...
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...
This paper considers the problem of reliability analysis of that consists groups of components organ...
With the increase of complex systems functions, the number of its components will rise. This will le...
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 ...
A Bayesian network (BN) is a powerful tool to represent the quantitative and qualitative features of...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
abstract: A quantitative analysis of a system that has a complex reliability structure always involv...
There are many methods applied including Bayesian network and D-S evidence theory to cope with uncer...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
In this paper, system reliability allocation using BN(Bayesian Network) was researched. The relation...
abstract: Bayesian networks are powerful tools in system reliability assessment due to their flexibi...
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...
This paper considers the problem of reliability analysis of that consists groups of components organ...
With the increase of complex systems functions, the number of its components will rise. This will le...
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 ...
A Bayesian network (BN) is a powerful tool to represent the quantitative and qualitative features of...
In the reliability modeling field, we sometimes encounter systems with uncertain structures, and the...
abstract: A quantitative analysis of a system that has a complex reliability structure always involv...
There are many methods applied including Bayesian network and D-S evidence theory to cope with uncer...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
Bayesian belief nets (BBNs) provide an effective way of reasoning under uncertainty. They have a fir...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...