Neighborhood Systems and Variable Precision Generalized Rough Sets*

2017 ◽  
Vol 153 (3) ◽  
pp. 271-290 ◽  
Author(s):  
Yu-Ru Syau ◽  
En-Bing Lin ◽  
Churn-Jung Liau
Keyword(s):  
Rough Sets ◽  
Variable Precision ◽  
Generalized Rough Sets

On Variable Precision Generalized Rough Sets and Incomplete Decision Tables

2021 ◽  
Vol 179 (1) ◽  
pp. 75-92
Author(s):  
Yu-Ru Syau ◽  
Churn-Jung Liau ◽  
En-Bing Lin
Keyword(s):  
Rough Set ◽  
Rough Sets ◽  
Decision Table ◽  
Necessary Condition ◽  
Weak Consistency ◽  
Decision System ◽  
Variable Precision ◽  
Generalized Rough Set ◽  
Decision Tables ◽  
Generalized Rough Sets

We present variable precision generalized rough set approach to characterize incomplete decision tables. We show how to determine the discernibility threshold for a reflexive relational decision system in the variable precision generalized rough set model. We also point out some properties of positive regions and prove a statement of the necessary condition for weak consistency of an incomplete decision table. We present two examples to illustrate the results obtained in this paper.

Relationships among generalized rough sets in six coverings and pure reflexive neighborhood system

2012 ◽  
Vol 207 ◽  
pp. 66-78 ◽  
Author(s):  
Lijuan Wang ◽  
Xibei Yang ◽  
Jingyu Yang ◽  
Chen Wu
Keyword(s):  
Rough Sets ◽  
Neighborhood System ◽  
Generalized Rough Sets

scholarly journals On Some Types of Covering-Based ℐ , T -Fuzzy Rough Sets and Their Applications

2021 ◽  
Vol 2021 ◽  
pp. 1-18
Author(s):  
Mohammed Atef ◽  
José Carlos R. Alcantud ◽  
Hussain AlSalman ◽  
Abdu Gumaei
Keyword(s):  
Rough Set ◽  
Rough Sets ◽  
Practical Application ◽  
Fuzzy Rough Sets ◽  
Fuzzy Rough Set ◽  
Lower Approximation ◽  
Upper Approximation ◽  
Numerical Example ◽  
Variable Precision

The notions of the fuzzy β -minimal and maximal descriptions were established by Yang et al. (Yang and Hu, 2016 and 2019). Recently, Zhang et al. (Zhang et al. 2019) presented the fuzzy covering via ℐ , T -fuzzy rough set model ( FC ℐ T FRS ), and Jiang et al. (Jiang et al., in 2019) introduced the covering through variable precision ℐ , T -fuzzy rough sets ( CVP ℐ T FRS ). To generalize these models in (Jiang et al., 2019 and Zhang et al. 2019), that is, to improve the lower approximation and reduce the upper approximation, the present paper constructs eight novel models of an FC ℐ T FRS based on fuzzy β -minimal (maximal) descriptions. Characterizations of these models are discussed. Further, eight types of CVP ℐ T FRS are introduced, and we investigate the related properties. Relationships among these models are also proposed. Finally, we illustrate the above study with a numerical example that also describes its practical application.

Generalized rough sets based feature selection

2000 ◽  
Vol 4 (1) ◽  
pp. 3-17 ◽  
Author(s):  
Mohamed Quafafou ◽  
Moussa Boussouf
Keyword(s):  
Feature Selection ◽  
Rough Sets ◽  
Generalized Rough Sets
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