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International Journal of Machine Learning and Cybernetics

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23-05-2017 | Original Article

Using single axioms to characterize (S, T)-intuitionistic fuzzy rough approximation operators

Authors: Wei-Zhi Wu, Ming-Wen Shao, Xia Wang

Published in: International Journal of Machine Learning and Cybernetics | Issue 1/2019

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Abstract

In this paper axiomatic characterizations of relation-based intuitionistic fuzzy rough approximation operators determined by an intuitionistic fuzzy triangular norm T and its dual intuitionistic fuzzy triangular conorm S on \([0, 1]\times [0, 1]\) are proposed. The constructive definitions and properties of S-lower and T-upper intuitionistic fuzzy rough approximation operators are first introduced. Operator-oriented characterizations of (S, T)-intuitionistic fuzzy rough approximation operators are then explored. Different sets of independent axioms for characterizing the essential properties of (S, T)-intuitionistic fuzzy rough approximation operators generated by various intuitionistic fuzzy relations are presented. Finally, it is examined that these sets of axioms can all be replaced by single axioms.

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Title: Using single axioms to characterize (S, T)-intuitionistic fuzzy rough approximation operators
Authors: Wei-Zhi Wu
Ming-Wen Shao
Xia Wang
Publication date: 23-05-2017
Publisher: Springer Berlin Heidelberg
Published in: International Journal of Machine Learning and Cybernetics / Issue 1/2019
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI: https://doi.org/10.1007/s13042-017-0696-2

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