Attribute Reduction Of Fuzzy Concept Lattice Based On The R 0 Implication Operator

In this paper, we investigate attribute reduction of fuzzy concept lattice based on the Ro implication operator. The first part of this paper is a comparative study on the methods of attribute reduction in rough set and concept lattice. It points out the common methods employed in attribute re-duction, the application scope of various methods, and their advantages and disadvantages. The exploration of these methods provides a reference train of thought for the future research of attribute reduction in fuzzy concept lat-tice. The second part studies the attribute reduction of fuzzy concept lattice by using variable precision concept lattice and A cut set formal context. It proposes an attribute reduction method based on the attribute characteris-tic of fuzzy concept lattice. At the same time, it analyzes the existing error when we transform fuzzy formal context into classic formal context based on various precision, and also gives out the evaluation criterion for judging the precision. The third part discusses the attribute reduction of fuzzy decision formal context under the strong partial ordering relation and the weak partial ordering relation, respectively. It gives out several characterization theorem of coordination set and an attribute reduction method of fuzzy decision formal context, achieving the purpose of simplifying fuzzy decision formal context. Thus, it is better to dig out the association rules from fuzzy decision formal context.