Upper Approximation Reduction Based on Intuitionistic Fuzzy $\mathcal{T}$ Equivalence Information Systems

2012 ◽  
pp. 55-62 ◽  
Author(s):  
Weihua Xu ◽  
Yufeng Liu ◽  
Wenxin Sun
Keyword(s):  
Information Systems ◽  
Upper Approximation ◽  
Intuitionistic Fuzzy

scholarly journals Rough Intuitionistic Fuzzy Information Systems

2013 ◽  
Vol 5 (4) ◽  
pp. 445-458 ◽  
Author(s):  
B. Davvaz ◽  
M. Jafarzadeh
Keyword(s):  
Information Systems ◽  
Fuzzy Information ◽  
Intuitionistic Fuzzy

Model of Covering Rough Sets in the Machine Intelligence

2012 ◽  
Vol 548 ◽  
pp. 735-739
Author(s):  
Hong Mei Nie ◽  
Jia Qing Zhou
Keyword(s):  
Information Systems ◽  
Set Theory ◽  
Rough Set ◽  
Equivalence Relation ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Machine Intelligence ◽  
Upper Approximation ◽  
Generalized Rough Sets

Rough set theory has been proposed by Pawlak as a useful tool for dealing with the vagueness and granularity in information systems. Classical rough set theory is based on equivalence relation. The covering rough sets are an improvement of Pawlak rough set to deal with complex practical problems which the latter one can not handle. This paper studies covering-based generalized rough sets. In this setting, we investigate common properties of classical lower and upper approximation operations hold for the covering-based lower and upper approximation operations and relationships among some type of covering rough sets.

ON ATTRIBUTE REDUCTION WITH INTUITIONISTIC FUZZY ROUGH SETS

2012 ◽  
Vol 20 (01) ◽  
pp. 59-76 ◽  
Author(s):  
ZHIMING ZHANG ◽  
JINGFENG TIAN
Keyword(s):  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Theoretical Foundation ◽  
Attribute Reduction ◽  
Upper Approximation ◽  
Intuitionistic Fuzzy ◽  
Intuitionistic Fuzzy Rough Sets ◽  
Axiomatic Approaches

Intuitionistic fuzzy (IF) rough sets are the generalization of traditional rough sets obtained by combining the IF set theory and the rough set theory. The existing research on IF rough sets mainly concentrates on the establishment of lower and upper approximation operators using constructive and axiomatic approaches. Less effort has been put on the attribute reduction of databases based on IF rough sets. This paper systematically studies attribute reduction based on IF rough sets. Firstly, attribute reduction with traditional rough sets and some concepts of IF rough sets are reviewed. Then, we introduce some concepts and theorems of attribute reduction with IF rough sets, and completely investigate the structure of attribute reduction. Employing the discernibility matrix approach, an algorithm to find all attribute reductions is also presented. Finally, an example is proposed to illustrate our idea and method. Altogether, these findings lay a solid theoretical foundation for attribute reduction based on IF rough sets.

Topological Approaches to the Second Type of Covering-Based Rough Sets

2011 ◽  
Vol 204-210 ◽  
pp. 1781-1784
Author(s):  
Bin Chen
Keyword(s):  
Data Mining ◽  
Information Systems ◽  
Rough Sets ◽  
Relative Interior ◽  
Upper Approximation ◽  
Definition Of ◽  
The Relationship

Rough sets, a tool for data mining, deal with the vagueness and granularity in information systems. This paper studies covering-based rough sets from the topological view. We explore the relationship between the relative closure and the second type of covering upper approximation. The major contributions of this paper are that we use the definition of the relative closure and the relative interior to discuss the conditions under which the relative operators satisfy certain classical properties. The theorems we get generalize some of the results in Zhu’s paper.

Intuitionistic Fuzzy Multicriteria Group Decision for Evaluating and Selecting Information Systems Projects

2013 ◽  
Vol 12 (13) ◽  
pp. 2505-2511 ◽  
Author(s):  
Beiling Ma ◽  
Chunqiao Tan ◽  
Zhong-Zhong Jiang ◽  
Hepu Deng
Keyword(s):  
Information Systems ◽  
Group Decision ◽  
Intuitionistic Fuzzy
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