2011•Journal of Chinese Computer SystemsRequires access

Heuristic Algorithm for Attribute Reduction on Granular Matrix

Su Yong-chang

Abstract

Attribute reduction is one of important issues in rough set theory.Based on rough set theory,this paper establishes the granular matrix with the idea of granular computing,defines the AND operation of granular matrix,presents the knowledge granulation method based on granular matrix and proposes an attribute reduction algorithm.The attribute reduction,using granular matrix to select the minimal attribute set,is different from the traditional attribute reduction which acquires the attribute kernel at first and then selects the best attribute set.Theoretical analysis shows that the new algorithm is reliable and valid.The algorithm could provide a new paradigm for the attribute reduction of granular computing and a feasible method for further research on granular computing.

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Key concepts: Granular computing, Rough set, Reduction (mathematics), Computer science, Attribute domain, Matrix (chemical analysis), Algorithm, Set (abstract data type)