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基于粗糙集的故障案例特征提取方法
Feature Attribute Extraction of Fault Case Based on Rough Sets
【摘要】 针对故障案例特征属性提取在故障案例推理中的重要性,提出了案例的决策表表示形式,介绍了Semi-Naive-Scaler属性离散化算法,并给出了基于遗传算法的属性约简算法。在粗糙集的基本理论和方法基础上,计算了特征属性的重要度,给出了计算实例。
【Abstract】 Feature attribute extraction of fault case is a very important aspect of fault case reasoning.The paper proposes the form of case decision table,introduces the attribute discretization algorithm of the Semi-Naive-Scaler,and also gives attribute reducing algorithm based on genetic.Based on these theories and methods of rough sets,the importance of feature attribute is calculated,and an example of attribute importance calculation is given at the end of this paper.
- 【文献出处】 江南大学学报(自然科学版) ,Journal of Jiangnan University(Natural Science Edition) , 编辑部邮箱 ,2009年05期
- 【分类号】TP182
- 【被引频次】9
- 【下载频次】172