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On three types of LL-fuzzy ββ-covering-based rough sets

Published 13 May 2022 in cs.AI | (2206.11025v1)

Abstract: In this paper, we mainly construct three types of LL-fuzzy β\beta-covering-based rough set models and study the axiom sets, matrix representations and interdependency of these three pairs of LL-fuzzy β\beta-covering-based rough approximation operators. Firstly, we propose three pairs of LL-fuzzy β\beta-covering-based rough approximation operators by introducing the concepts such as β\beta-degree of intersection and β\beta-subsethood degree, which are generalizations of degree of intersection and subsethood degree, respectively. And then, the axiom set for each of these LL-fuzzy β\beta-covering-based rough approximation operator is investigated. Thirdly, we give the matrix representations of three types of LL-fuzzy β\beta-covering-based rough approximation operators, which make it valid to calculate the LL-fuzzy β\beta-covering-based lower and upper rough approximation operators through operations on matrices. Finally, the interdependency of the three pairs of rough approximation operators based on LL-fuzzy β\beta-covering is studied by using the notion of reducible elements and independent elements. In other words, we present the necessary and sufficient conditions under which two LL-fuzzy β\beta-coverings can generate the same lower and upper rough approximation operations.

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