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Variable precision intuitionistic fuzzy rough sets model and its application

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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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Acknowledgments

The authors would like to thank the referees and Professor Xizhao Wang, Editor-in-Chief, for providing very helpful comments and suggestions. This work is supported by National Natural Science Fund of China (71061013, 61262022), the Natural Scientific Fund of Gansu Province of China (1208RJZA251) and the Scientific Research Project of Northwest Normal University (NWNU-KJCXGC-03-61).

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Authors and Affiliations

  1. College of Mathematics and Statistics, Northwest Normal University, Lanzhou, 730070, PR China

    Zengtai Gong & Xiaoxia Zhang

Authors
  1. Zengtai Gong
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  2. Xiaoxia Zhang
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Correspondence to Zengtai Gong.

Additional information

This work is supported by National Natural Science Fund of China (71061013, 61262022), the Natural Scientific Fund of Gansu Province of China (1208RJZA251) and the Scientific Research Project of Northwest Normal University (NWNU-KJCXGC-03-61).

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Gong, Z., Zhang, X. Variable precision intuitionistic fuzzy rough sets model and its application. Int. J. Mach. Learn. & Cyber. 5, 263–280 (2014). https://doi.org/10.1007/s13042-013-0162-8

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  • DOI: https://doi.org/10.1007/s13042-013-0162-8

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