摘要
为了有效评估动态系统要素间的复杂行为和交互特性,提出了一种基于贝叶斯网络(Bayesian Network,BN)的可靠性建模与分析的新方法。该方法利用BN的不确定性推理和图形化表达的优势,能够很好地捕捉系统要素的行为与交互,以结构的方式组合各种基本BN架构为用户提供模块化和分级的途径对系统进行建模。实验结果表明该方法的可行性和有效性。从而提高了系统的灵敏度,减少了其不确定性。
In order to evaluate complex behaviors and interactions between their components of dynamic systems, a new method for modeling and analysing dynamic systems reliability based on BN was presented. By using the advantages of uncertainty reasoning and figurative expression of Bayesian network, system components＇ behaviors and interactions were captured well-defined. Combining, in a structured way, the various ＇basic＇ Bayesian network constructs enables the user to construct, in a modular and hierarchical fashion, the system model. Experiment results show that the method is feasible and valid. Sensitivity is improved, and uncertainty is lessened.
出处
《系统仿真学报》
CAS
CSCD
北大核心
2009年第16期4934-4937,共4页
Journal of System Simulation
