Attribute Reduction Of Three Kinds Of Information System Model

Rough set theory is a mathematical tool which deals with the fuzzy and uncer-tain and is proposed by Professor Pawlak, a scientist in Poland. Knowledge reduction is one of the core contents of rough set theory. As is well-known, the knowledge base describing the attributes of knowledge is not equally important, and even some of the properties are redundant. On the one hand, it resulted in the waste of resources; On the other hand, it can interfere with a person to make the right decision. Knowledge reduction, is to keep the classification ability of the knowledge base invariant conditions, and to delete the irrelevant or unimportant attributes, so that the knowledge is the simplified representation, which is what the person would expect.The main research contents of this paper are as follows:(1) In incomplete Bayesian decision information system, this paper improved the global gain function, and combined with the coding method of binary discernibility matrix. A new heuristic attribute reduction algorithm was proposed. The method was applied to the study of the system of the fault condition’s diagnosis, and improved the efficiency of reduction.(2) In incomplete intuitionistic fuzzy information system, the new improved model was proposed. Firstly, through introduce the closeness degree, then defined the rate of closeness. Concurrently, the model is expansions of the tolerance relation. Based on the double preci-sion tolerance of the closeness degree and the rate of closeness is proposed. And the matrix representation of the close rate is given. Secondly, information entropy theory is introduced, then one kind based on mutual information incomplete intuitionistic fuzzy decision information system attribute reduction algorithm was proposed. Finally, through the illustrate to verify the effectiveness of the algorithm.(3)By considering that optimistic rough set is too loose while pessimistic rough set is too strict, the fusion of multigranulation rough set, variable precision rough set and the incomplete interval valued decision information system is presented.On the basis of the limited dominance relation based variable precision rough set and multigranulation rough set, the concept of vari- able precision multigranulation rough set is proposed, which includes variable precision opti-mistic and pessimistic rough sets. Then the properties, the approximate accuracy and roughness about the new model are discussed. Defined the concept of model attribute importance degree.