DocumentCode :
2700056
Title :
Application of fuzzy rough sets in patterns recognition of bearing
Author :
Tian, Hao ; Kang, Xiao-Yong ; Zhang, Jun-Nuo ; Han, Shan-Shan
Author_Institution :
Dept. of Guns Eng., Ordnance Eng. Coll., Shijiazhuang, China
fYear :
2012
fDate :
15-18 June 2012
Firstpage :
731
Lastpage :
734
Abstract :
A method of patterns recognition was presented based on fuzzy rough sets. Dynamic clustering algorithm and method of analysis of variance is introduced to fuzzify the continuous condition attribute, and fuzzy membership functions is derived, which avoided losing information caused by discretization in rough set theory. F test is introduced to judge the valid analysis of clustering, which has overcome the disadvantage of determining artificially the class number of clustering. The fuzzy decision table obtained by attribute fuzzified is used to attributes reduction, then values of attributes are reducted, and clear and concise pattern rules are obtained. The application showed that the proposed algorithm can effective improve the pattern recognition accuracy.
Keywords :
decision tables; fuzzy set theory; machine bearings; pattern recognition; rough set theory; analysis of variance; attributes reduction; bearing; continuous condition attribute; dynamic clustering algorithm; fuzzy decision table; fuzzy membership functions; fuzzy rough sets; pattern recognition; rough set theory; Educational institutions; Fault diagnosis; Fuzzy sets; Heuristic algorithms; Pattern recognition; Rough sets; anaiysis of variance; attribute reduction; dynamic clustering; fuzzy-rough sets; patterns recognition;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Quality, Reliability, Risk, Maintenance, and Safety Engineering (ICQR2MSE), 2012 International Conference on
Conference_Location :
Chengdu
Print_ISBN :
978-1-4673-0786-4
Type :
conf
DOI :
10.1109/ICQR2MSE.2012.6246333
Filename :
6246333
Link To Document :
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