Reasoning Based on Rough Set in Decision Making

The rough sets theory has prove to be a very useful tool for analysis of information tables describing objects by means of disjoint subsets of condition and decision attributes. The key idea of rough sets is approximation of knowledge expressed by decision attributes using knowledge expressed by condition attributes. In real life the decision and condition concepts are often fuzzy and be described by fuzzy sets. 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 level approximation are given, and propose the idea of multiple approximation spaces for decision making. We discuss the relationship between condition and decision attributes with some examples. This offered theoretical foundation for assigning the weights to condition attributes during decision making.