Multi-source Knowledge Acquisition Model based on Rough Set

2014 ◽  
Vol 13 (7) ◽  
pp. 1386-1390
Author(s):  
Li Li ◽  
Lu Sun ◽  
Jiayang Wang
2007 ◽  
Vol 359-360 ◽  
pp. 518-522
Author(s):  
Wan Shan Wang ◽  
Tian Biao Yu ◽  
Xing Yu Jiang ◽  
Jian Yu Yang

Remote control and fault diagnosis of ultrahigh speeding grinding is studied, which is based on the theory of rough set. Knowledge acquisition and reduction rule of fault diagnosis, realization method of remote control for ultrahigh speed grinding are studied, diagnosis model is established. Based on the theoretical research and ultrahigh speed grinder with a linear speed of 250 m/s, the remote control and fault diagnosis system of ultrahigh speed grinding is developed. Results of the system running show that the environment is improved, the mental pressure of workers is relieved and the efficiency is improved. At the same time, it proves that the ability to diagnosis and the accuracy of diagnosis for the ultrahigh speed grinding are improved and the time for diagnosis is shortened by applying rough set.


2011 ◽  
Vol 15 ◽  
pp. 1947-1951
Author(s):  
Yu-Ming Zhai ◽  
Rui-Xia Yan ◽  
Hai-Feng Liu
Keyword(s):  

2013 ◽  
Vol 694-697 ◽  
pp. 2856-2859
Author(s):  
Mei Yun Wang ◽  
Chao Wang ◽  
Da Zeng Tian

The variable precision probabilistic rough set model is based on equivalent relation and probabilistic measure. However, the requirements of equivalent relation and probabilistic measure are too strict to satisfy in some practical applications. In order to solve the above problem, a variable precision rough set model based on covering relation and uncertainty measure is proposed. Moreover, the upper and lower approximation operators of the proposed model are given, while the properties of the operators are discussed.


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