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International Journal of Machine Learning and Cybernetics
Published in: International Journal of Machine Learning and Cybernetics 2/2014

01-04-2014 | Original Article

Variable precision intuitionistic fuzzy rough sets model and its application

Authors: Zengtai Gong, Xiaoxia Zhang

Published in: International Journal of Machine Learning and Cybernetics | Issue 2/2014

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Abstract

Rough set theory is an important mathematical tool to deal with insufficient and incomplete information. The concepts of intuitionistic fuzzy rough sets and variable precision rough sets are very useful in the study of intelligent systems. The aim of this paper is to present a new extension of the rough set theory by means of integrating the variable precision rough set theory with the intuitionistic fuzzy rough set theory, i.e., the variable precision intuitionistic fuzzy rough set model is presented based on the intuitionistic fuzzy inclusion sets and intuitionistic fuzzy inclusion ratio which are defined in this paper, and by employing the intuitionistic fuzzy implicator and the intuitionistic fuzzy t-norm. Meanwhile, the approximation quality and attribute reduction of the variable precision intuitionistic fuzzy rough sets are defined. It shows that the results obtained in this paper extend the previous related conclusions. Finally, an example is given to illustrate our results.
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Metadata
Title
Variable precision intuitionistic fuzzy rough sets model and its application
Authors
Zengtai Gong
Xiaoxia Zhang
Publication date
01-04-2014
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 2/2014
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-013-0162-8

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