[1]石金彦,黄士涛,雷文平..粗糙集与决策树结合诊断故障的数据挖掘方法[J].郑州大学学报(工学版),2003,24(01):109-112.[doi:10.3969/j.issn.1671-6833.2003.01.027]
 Shi Jinyan,HUANG Shitao,Raven Ping.A data mining method that combines rough sets with decision trees to diagnose failures[J].Journal of Zhengzhou University (Engineering Science),2003,24(01):109-112.[doi:10.3969/j.issn.1671-6833.2003.01.027]
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粗糙集与决策树结合诊断故障的数据挖掘方法()
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《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]

卷:
24
期数:
2003年01期
页码:
109-112
栏目:
出版日期:
1900-01-01

文章信息/Info

Title:
A data mining method that combines rough sets with decision trees to diagnose failures
作者:
石金彦黄士涛雷文平.
郑州大学机械工程学院,河南,郑州,450002, 郑州大学机械工程学院,河南,郑州,450002, 郑州大学机械工程学院,河南,郑州,450002
Author(s):
Shi Jinyan; HUANG Shitao; Raven Ping
关键词:
数据挖掘 故障诊断 关联规则 粗糙集 决策树
Keywords:
DOI:
10.3969/j.issn.1671-6833.2003.01.027
文献标志码:
A
摘要:
根据数据挖掘技术用于故障诊断的基本思想,利用粗糙集进行数据归纳,过滤大量故障数据中的冗余属性,得到精简故障数据集.而后,用决策树分类方法处理精简数据集,产生分类所需的规则以进行分类,并结合实例说明了该方法的工作步骤.由实例可知该方法用于故障诊断的可行性,最后指出实际应用过程中的一些技术难题.
Abstract:
According to the basic idea of data mining technology for fault diagnosis, rough sets are used to summarize data, filter redundant attributes in a large number of fault data, and obtain a simplified fault data set. Then, the decision tree classification method is used to process the refined dataset, and the rules required for classification are generated for classification, and the working steps of the method are illustrated with examples. The feasibility of this method for fault diagnosis can be seen from the examples, and finally some technical problems in the actual application process are pointed out.

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更新日期/Last Update: 1900-01-01