摘要
贝叶斯网络计算量随着节点数增多呈指数增长,限制了大规模贝叶斯网络在安全性分析中的应用。为此,利用独立性条件分解整个网络,压缩推理时显式表达的项数,给出了计算顶事件发生概率及割集的算法,并分析了算法复杂性。在满足工程需要情况下,将提出算法与基于BDD算法相比,该算法表现出占用内存少、运行速度快的良好性能。
The computation consumption of Bayesian network increases exponentially with the nodes number and that limits the application of large-scale Bayesian network.In order to relieve this situation,this paper makes use of the independence condition to decompose the whole Bayesian network according to the characteristics of safety analysis,compresses the items number in reasoning process,proposes the algorithms for top event probability and cut sets,simultaneously analyses the computational complexity.Compared with BDD-based FTA algorithm,the proposed algorithms showed a lower memory demand and a higher speed performance when meeting the need of safety engineering.
出处
《国防科技大学学报》
EI
CAS
CSCD
北大核心
2007年第4期130-134,共5页
Journal of National University of Defense Technology
基金
国家部委基金资助项目(2005AA845023)
关键词
贝叶斯网络
安全性分析
割集
条件独立
bayesian network
safety analysis
cut set
conditional independence
作者简介
董豆豆（1976-），男，博士生。
