摘要
Causal reasoning plays an important role in situation assessment (SA). Using Bayesian networks to find out the hidden patterns between situation hypothesis and events is the function needed to accomplish in situation as sessment. Based on different link relationship,a Bayesian network model for situation assessment is analyzed in this paper. To overcome the weakness of this model in application for dynamic changed scenario ,this paper presents an approach that uses a dynamic Bayesian network to represent features of the situation hypothesis and events. And the algorithms of propagation of corresponding information through the network are introduced respectively.
Causal reasoning plays an important role in situation assessment (SA). Using Bayesian networks to find out the hidden patterns between situation hypothesis and events is the function needed to accomplish in situation assessment. Based on different link relationship,a Bayesian network model for situation assessment is analyzed in this paper. To overcome the weakness of this model in application for dynamic changed scenario,this paper presents an approach that uses a dynamic Bayesian network to represent features of the situation hypothesis and events. And the algorithms of propagation of corresponding information through the network are introduced respectively.
出处
《计算机科学》
CSCD
北大核心
2002年第11期50-52,共3页
Computer Science
基金
国防科技预研基金(00J6.6.1 DZ0103)
关键词
态势评估
因果推理
贝叶斯网络
不确定性
神经网络
Bayesian networks, Dynamic Bayesian net works, Situation assessment, Events
