Composed fuzzy rough set and its applications in fuzzy RSAR

Authors:
Weigen Qiu;Zhibin Hu
Affiliations:
Computer Faculty of GuangDong University of Technology, GuangZhou, GuangDong, P.R. China and State Key Laboratory of Intelligent Technology & Systems, Department of Computer Science & Technology, ...;Computer Faculty of GuangDong University of Technology, GuangZhou, GuangDong, P.R. China
Venue:
APPT'07 Proceedings of the 7th international conference on Advanced parallel processing technologies
Year:
2007

Citing 3
Cited 0

Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory

Intelligent Decision Support: Handbook of Applications and Advances of the Rough Sets Theory
Generalized fuzzy rough sets

Information Sciences—Informatics and Computer Science: An International Journal
A comparative study of fuzzy sets and rough sets

Information Sciences: an International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Pawlak rough set theory is a powerful mathematic tool to deal with imprecise, uncertainty and incomplete dataset. In this paper, we study the fuzzy rough set attribute reduction (fuzzy RSAR) in fuzzy information systems. Firstly, we present the formal definition of a kind new rough set form-the composed fuzzy rough set. The second, some properties of extension forms of Pawlak rough set are also discussed. Lastly, we illustrate the fuzzy RSAR based on composed fuzzy rough set, and a simple example is given to show this approach can retain less attributes and entailing higher classification accuracy than the crisp RST-based reduction method.