The fuzzy concept based on approximation space in decision-making

Abstract

Rough set theory refers to classification of objects are described by well-defined values of qualitative and quantitative attributes. In practice, however, the decision and condition attributes are often fuzzy and be described by fuzzy sets. This situation may be formally modeled by similarity or tolerance relations instead of the indiscernibility relation. This paper investigates a new method for decision making system that derives from the combination of rough sets and fuzzy sets. The concept of inclusion degree of fuzzy sets and multiple approximation space are given. We propose the idea of multiple approximation spaces for decision making, and discussing the relationship between condition and decision attributes and the assignment of condition attributes weights for each decision attribute.