Rough Sets Based Incremental Rule Acquisition in Set-Valued Information Systems

2012 ◽  
pp. 135-146
Author(s):  
Junbo Zhang ◽  
Tianrui Li ◽  
Da Ruan
Keyword(s):  
Information Systems ◽  
Rough Sets ◽  
Rule Acquisition

α-Dominance relation and rough sets in interval-valued information systems

2015 ◽  
Vol 294 ◽  
pp. 334-347 ◽  
Author(s):  
Xibei Yang ◽  
Yong Qi ◽  
Dong-Jun Yu ◽  
Hualong Yu ◽  
Jingyu Yang
Keyword(s):  
Information Systems ◽  
Rough Sets ◽  
Dominance Relation ◽  
Interval Valued

Soft dominance based rough sets with applications in information systems

2019 ◽  
Vol 113 ◽  
pp. 171-195 ◽  
Author(s):  
Abbas Ali ◽  
Muhammad Irfan Ali ◽  
Noor Rehman
Keyword(s):  
Information Systems ◽  
Rough Sets

Soft Computing for Evolutionary Information Systems — Potentials of Rough Sets

2000 ◽  
pp. 481-494 ◽  
Author(s):  
A. B. Patki ◽  
G. V. Raghunathan ◽  
Soumik Ghosh ◽  
S. Sivasubramanian ◽  
Azar Khurshid
Keyword(s):  
Information Systems ◽  
Soft Computing ◽  
Rough Sets ◽  
Evolutionary Information

scholarly journals Reduction of Neighborhood-Based Generalized Rough Sets

2011 ◽  
Vol 2011 ◽  
pp. 1-22 ◽  
Author(s):  
Zhaohao Wang ◽  
Lan Shu ◽  
Xiuyong Ding
Keyword(s):  
Information Systems ◽  
Set Theory ◽  
Rough Set ◽  
Rough Sets ◽  
Rough Set Theory ◽  
Open Problems ◽  
The Third ◽  
Generalized Rough Sets

Rough set theory is a powerful tool for dealing with uncertainty, granularity, and incompleteness of knowledge in information systems. This paper discusses five types of existing neighborhood-based generalized rough sets. The concepts of minimal neighborhood description and maximal neighborhood description of an element are defined, and by means of the two concepts, the properties and structures of the third and the fourth types of neighborhood-based rough sets are deeply explored. Furthermore, we systematically study the covering reduction of the third and the fourth types of neighborhood-based rough sets in terms of the two concepts. Finally, two open problems proposed by Yun et al. (2011) are solved.

Communication Between Information Systems Using Fuzzy Rough Sets

2013 ◽  
Vol 21 (3) ◽  
pp. 527-540 ◽  
Author(s):  
E. C. C. Tsang ◽  
Changzhong Wang ◽  
Degang Chen ◽  
Congxin Wu ◽  
Qinghua Hu
Keyword(s):  
Information Systems ◽  
Rough Sets ◽  
Fuzzy Rough Sets

Uncertainty measures of rough sets based on discernibility capability in information systems

2017 ◽  
Vol 21 (4) ◽  
pp. 1081-1096 ◽  
Author(s):  
Shuhua Teng ◽  
Fan Liao ◽  
Yanxin Ma ◽  
Mi He ◽  
Yongjian Nian
Keyword(s):  
Information Systems ◽  
Rough Sets ◽  
Uncertainty Measures

Knowledge acquisition in vague objective information systems based on rough sets

2010 ◽  
Vol 27 (2) ◽  
pp. 129-142 ◽  
Author(s):  
Lin Feng ◽  
Guo-Yin Wang ◽  
Xin-Xin Li
Keyword(s):  
Information Systems ◽  
Knowledge Acquisition ◽  
Rough Sets ◽  
Objective Information ◽  
Vague Objective
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