基于QDFS算法的多值属性系统诊断策略

Zhou Deyun, L. Xiaofeng, Ma Ling
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引用次数: 0

摘要

研究了多值属性系统的诊断策略问题。基于准深度优先搜索(quasi-depth first search, QDFS)算法改进信息启发式算法的主要特点,将QDFS算法用于改进基于信息熵的多值属性系统诊断策略。然后,提出了一种新的多值属性系统诊断策略。理论和实验表明,该方法在优化结果和计算复杂度上都明显优于信息熵算法,可用于设计复杂多值属性系统的最优诊断策略。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Diagnostic strategy for multi-value attribute system based on QDFS algorithm
In this paper, the problem of diagnostic strategy for multi-value attribute system is considered. Based on the principal characteristics that quasi-depth first search (QDFS) algorithm can improve the information heuristic algorithm, QDFS is used to improve the information entropy based diagnostic strategy for multi-value attribute system. Then, a new diagnostic strategy for multi-value attribute system is proposed. The theory and experiment demonstrate that, this method is much better than information entropy algorithm on optimization results and computational complexity, which can be used to design the optimal diagnostic strategy for complicated multi-value attribute systems.
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