Journal
INTERNATIONAL JOURNAL OF MACHINE LEARNING AND CYBERNETICS
Volume 5, Issue 2, Pages 263-280Publisher
SPRINGER HEIDELBERG
DOI: 10.1007/s13042-013-0162-8
Keywords
Intuitionistic fuzzy rough sets; Intuitionistic fuzzy inclusion sets; Intuitionistic fuzzy inclusion ratio; Variable precision intuitionistic fuzzy rough sets; Approximation quality; Attribute reduction
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Funding
- National Natural Science Fund of China [71061013, 61262022]
- Natural Scientific Fund of Gansu Province of China [1208RJZA251]
- Scientific Research Project of Northwest Normal University [NWNU-KJCXGC-03-61]
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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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