Pawlak Rough Set Model, Medical Reasoning and Rule Mining

2006 ◽  
pp. 53-70 ◽  
Author(s):  
Shusaku Tsumoto
Keyword(s):  
Rough Set ◽  
Rule Mining ◽  
Medical Reasoning

A Fault Diagnosis Model for Power Transformer Using Association Rule Mining-Based on Rough Set

2014 ◽  
Vol 519-520 ◽  
pp. 1169-1172
Author(s):  
De Wen Wang ◽  
Lin Xiao He
Keyword(s):  
Fault Diagnosis ◽  
Rough Set ◽  
Association Rule ◽  
Association Rule Mining ◽  
Power Transformer ◽  
Monitoring Data ◽  
Rule Mining ◽  
Monitoring Technology ◽  
On Line ◽  
Diagnosis Model

With the development of on-line monitoring technology of electric power equipment, and the accumulation of both on-line monitoring data and off-line testing data, the data available to fault diagnosis of power transformer is bound to be massive. How to utilize those massive data reasonably is the issue that eagerly needs us to study. Since the on-line monitoring technology is not totally mature, which resulting in incomplete, noisy, wrong characters for monitoring data, so processing the initial data by using rough set is necessary. Furthermore, when the issue scale becomes larger, the computing amount of association rule mining grows dramatically, and its easy to cause data expansion. So it needs to use attribute reduction algorithm of rough set theory. Taking the above two points into account, this paper proposes a fault diagnosis model for power transformer using association rule mining-based on rough set.

Multi-level rough set reduction for decision rule mining

2013 ◽  
Vol 39 (3) ◽  
pp. 642-658 ◽  
Author(s):  
Mingquan Ye ◽  
Xindong Wu ◽  
Xuegang Hu ◽  
Donghui Hu
Keyword(s):  
Decision Rule ◽  
Rough Set ◽  
Rule Mining ◽  
Multi Level
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