[1]DENG Tingquan,YANG Chengdong,et al.Fuzzy similarity relation based variable precision fuzzy rough sets[J].CAAI Transactions on Intelligent Systems,2012,7(2):148-152.
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Fuzzy similarity relation based variable precision fuzzy rough sets

CAAI Transactions on Intelligent Systems[ISSN 1673-4785/CN 23-1538/TP] Volume: 7 Number of periods: 2012 2 Page number: 148-152 Column: 学术论文—人工智能基础 Public date: 2012-04-25
Title:
Fuzzy similarity relation based variable precision fuzzy rough sets
Author(s):
DENG Tingquan1;  2;  YANG Chengdong2;  3;  ZHANG Yuetong1
1. College of Science, Harbin Engineering University, Harbin 150001, China;
?2. College of Computer Science and Technology, Harbin Engineering University, Harbin 150001, China;
3. School of Informatics, Linyi University, Linyi 276000, China
Keywords:
variable precision rough sets;  fuzzy similarity relation;  relative error rates of classification;  fuzzy logical operator;  fuzzy rough sets
CLC:
TPl8; TP301
DOI:
-
Abstract:
A classical variable precision fuzzy rough set was built on the basis of fuzzy equivalent relationships. Nonetheless, it is hard to directly obtain the fuzzy equivalent relationships, which are usually replaced by a closure of fuzzy equivalent relationships, and this method causes a loss of much valuable information and increases the computation complexity in the application of the fuzzy rough set. This paper first took advantage of a fuzzy logical operator to construct fuzzy relative error rates of classification, and then proposed a variable precision fuzzy rough set model based on fuzzy similarity relationships. Moreover, the properties of this model were investigated. On the one hand, the model is able to deal with noise data with the advantages of variable precision rough sets; on the other hand, since it is based on fuzzy similarity relationships, the model could be applied more widely. 
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