Multi-adjoint intuitionistic fuzzy rough sets

Meishe Liang; Jusheng Mi; Tao Feng; Tianna Zhao

Multi-adjoint intuitionistic fuzzy rough sets

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Author(s): Meishe Liang^{1, 2} ; Jusheng Mi¹ ; Tao Feng³ ; Tianna Zhao¹
- Affiliations: 1: College of Mathematics and Information Science , Hebei Normal University , Shijiazhuang 050024 , People's Republic of China ;
  2: Department of Scientific Development and School-Business Cooperation , Shijiazhuang University of Applied Technology , Shijiazhuang 050081 , People's Republic of China ;
  3: College of Science , Hebei University of Science and Technology , Shijiazhuang 050018 , People's Republic of China
Source: Volume 2018, Issue 16, November 2018, p. 1637 – 1644
DOI: 10.1049/joe.2018.8298 , Online ISSN 2051-3305

This is an open access article published by the IET under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)

Received 18/07/2018, Accepted 02/08/2018, Revised 01/08/2018, Published 16/08/2018

The combination of fuzzy information systems (ISs) and multi-adjoint theory has become a hot issue in the study and applications of artificial intelligence. An intuitionistic fuzzy set has more flexible and practical ability to represent information and is better in dealing with ambiguity and uncertainty when compared with the fuzzy set. Multi- adjoint intuitionistic fuzzy rough sets are constructed by using adjoint triples under intuitionistic fuzzy IS. For this purpose, the authors propose intuitionistic fuzzy indiscernibility relation and multi-adjoint approximation operators. The basic results in the multi-adjoint fuzzy rough set model are generalised to multi-adjoint intuitionistic fuzzy rough set model. The analogous results are also verified. After that, a novel approach of attribute reduction is proposed. First, a kind of approximate reduction to keep the dependence of the positive region to a degree $α$ is formulated. Second, they propose a heuristic algorithm to compute the attribute reduction. At last, they employ an example to describe the processing of the algorithm.

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