By the B-cut sets and the probabilities of the nodes of Binary Decision Diagrams (BDD), a new quantitative analysis algorithm of coherent fault tree based on BDD is presented in this paper.

利用二元决策图(BDD)中的B—割集和节点概率，提出了基于BDD的关联故障树定量分析新算法。

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At last, a binary decision tree could be built. Algorithm analysis and simulation results show that RMBRDM can support rules with ranges and the performance of RMBRDM is better than that of PTS.

最后建立一棵二叉决策树。理论分析和仿真实验均表明，RMBRDM算法不仅支持以范围形式表示的规则，且时空性能优于PTS算法。

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Finally, the experiment process is introduced, comparing with the binary decision tree based on minimum entropy heuristic information, the results show the algorithm proposed in this paper is valid.

最后，给出了实验过程，与用熵作启发式的二叉决策树的比较结果表明了本文算法的有效性。

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Finally, the experiment process is introduced, comparing with the binary decision tree based on minimum entropy heuristic information, the results show the algorithm proposed in this paper is valid.

最后，给出了实验过程，与用熵作启发式的二叉决策树的比较结果表明了本文算法的有效性。

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