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An algorithm to find minimal cuts of coherent fault-trees with event-classes using a decision tree

机译:一种使用决策树查找具有事件类的相干故障树的最小切割的算法

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摘要

A new algorithm (CS-MC) for computing the minimal cuts of s-coherent fault trees is presented.\udInput events of the fault tree are assumed classified into classes, where events of the same class are indistinguishable. This allows capturing some symmetries which some systems exhibit. CS-MC uses a decision tree. The search implemented by the decision tree is guided by heuristics which try to make CS-MC as efficient as possible. In addition, an irrelevance test on the inputs of the fault tree is used to prune the search. The performance of CS-MC is illustrated and compared with the basic top-down and bottom-up algorithms using a set of fault trees, some of which are very difficult. The CS-MC performs very well even in the difficult examples, and the memory requirements of CS-MC are small.
机译:提出了一种用于计算s相干故障树的最小割的新算法(CS-MC)。假定故障树的输入事件已分类,但同一类事件无法区分。这允许捕获某些系统表现出的某些对称性。 CS-MC使用决策树。由决策树执行的搜索由启发式方法指导,这些方法试图使CS-MC尽可能高效。另外,使用对故障树的输入的不相关性测试来修剪搜索。阐述了CS-MC的性能,并与使用一组故障树的基本自上而下和自下而上的算法进行了比较,其中有些非常困难。即使在困难的示例中,CS-MC的性能也非常好,并且CS-MC的内存需求很小。

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