关键词: 变结构离散动态贝叶斯网络（SVDDBN）, 缺失数据, 数据插补算法

Abstract:

It is more general to deal with the uncertainty of the Structure-Variable Discrete Dynamic Bayesian Network（SVDBN）. In order to overcome the problem that SVDDBN missing data leads to poor accuracy of reasoning results, a one-step prediction SVDDBN missing data interpolation algorithm is proposed. According to the law that the information can propagate along the time axis of the network to the next time slice, the filter value can be obtained by using the "mixed" information to update the reliability online, and then the posterior probability of the missing data node of the next time slice can be obtained as the interpolation value by further prediction. The simulation results show that the proposed algorithm can effectively interpolate missing data and improve the accuracy and reliability of SVDDBN inference.

Key words: Structure-Variable Discrete Dynamic Bayesian Network（SVDDBN）, missing data, data interpolation algorithm