An Interval Type-2 Fuzzy Rough Set Model for Attribute Reduction

Abstract

Rough set theory is a very useful tool for describing and modeling vagueness in ill-defined environments. Traditional rough set theory is restricted to crisp environments. However, nowadays, it has been extended to fuzzy environments, resulting in the development of the so-called fuzzy rough sets. Type-2 fuzzy sets possess many advantages over type-1 fuzzy sets, but for the general type-2 fuzzy sets, the computational complexity is severe. On the other hand, set-theoretic and arithmetic computations for the interval type-2 fuzzy sets are very simple. Motivated by the aforementioned accomplishments, in this paper, the concept of fuzzy rough sets is generalized to interval type-2 fuzzy environments. Subsequently, a method of attribute reduction within the interval type-2 fuzzy rough set framework is proposed. Lastly, the properties of the interval type-2 fuzzy rough sets are presented.