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中文摘要：
分析比较Shafer—Shenoy结构和Hugin结构两种经典的基于邻接树的贝叶斯网络推理算法．针对Hugin算法在推理分析领域的局限性，通过在Hugin算法的消息传播过程中引入零因子标志位和零因子处理机制，提出一种Hugin算法的改进算法R—Hugin．该算法具有良好的推理分析性能，并从理论和实验两个方面证明R—Hugin算法的正确性和有效性．
英文摘要：
Two classical junction-tree-based algorithms for reasoning in Bayesian network, Shafer-Shenoy architecture and Hugin architecture, are analyzed and compared. For the limitation of the Hugin algorithm in the reasoning analysis, a refined Hugin algorithm, R-Hugin, is proposed, which introduces the zero-factor flag and zero-factor processing mechanism in the message propagation process of the Hugin algorithm. R-Hugin algorithm has good reasoning and analyzing performance. Meanwhile, the correctness and efficiency of the R-Hugin algorithm are validated by theory and experiments.
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