A Matrix-Based Approach for Calculation of Knowledge Granulation
WANG Lei1,2,LI Tian-Rui1
1.School of Information Science Technology,Southwest Jiaotong University,Chengdu 610031 2.School of Information Engineering,Nanchang Institute of Technology,Nanchang 330099
Abstract The uncertainty is one of the hot issues in rough set theory. Knowledge granulation is a main approach to measure the uncertainty of knowledge systems. From the viewpoint of matrix,an approach for calculation of knowledge granulation,discernibility degree and attribute importance is studied,and the inherent meaning of matrix expression for the knowledge granulation is analyzed. Furthermore,the relations between the knowledge granulation and the equivalent relation matrix are revealed. Moreover,the hierarchical structure of knowledge granulation is proposed to discuss the variation of knowledge granulation under the addition or removal of a single attribute. Finally,combined with the update of the equivalent relation matrix under addition or removal of a signal attribute,the matrix-based computing method for attribute importance is applied in calculating the core set and the minimum attribute reduction. The numerical examples demonstrate the effectiveness of the proposed method on attribute reduction.
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2013, Vol. 26 
