一种改进的临界诊断推理方法

Yue Xu, Chengqi Zhang
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引用次数: 6

摘要

基于模型的诊断具有计算复杂度高的缺点。克服这一缺点的一种方法是将诊断集中在缩小的诊断空间上。我们在(Raiman et al., 1993)方法的基础上提出了一种改进的关键诊断推理方法。该方法的诊断重点是找出核心诊断,而不是全部诊断。我们给出了临界覆盖的更新定义,我们称之为“临界分区”。与临界覆盖条件相比,临界分区条件放宽。相应的,提出了一种非回溯算法——关键分区搜索算法(SCP)来查找关键分区。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An improved critical diagnosis reasoning method
Model-based diagnosis has the disadvantage of a high computational complexity. One way to overcome this disadvantage is to focus the diagnosis on a reduced diagnostic space. We propose an improved critical diagnosis reasoning method based on the method proposed by (Raiman et al., 1993). The method focuses the diagnosis on finding out the kernel diagnoses instead of the whole diagnoses. We give an updated definition of critical cover which we call "critical partition". The conditions satisfied by critical partition are relaxed compared with the conditions for critical cover. Correspondingly, a non-backtracking algorithm called Searching Critical Partition (SCP) to find out the critical partition is also proposed.
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