2010•International Journal of Cognitive Informatics and Natural IntelligenceRequires access

Approximations in Rough Sets vs Granular Computing for Coverings

Guilong Liu, William Zhu

Abstract

Rough set theory is an important technique in knowledge discovery in databases. Classical rough set theory proposed by Pawlak is based on equivalence relations, but many interesting and meaningful extensions have been made based on binary relations and coverings, respectively. This paper makes a comparison between covering rough sets and rough sets based on binary relations. This paper also focuses on the authors’ study of the condition under which the covering rough set can be generated by a binary relation and the binary relation based rough set can be generated by a covering.

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Key concepts: Rough set, Binary relation, Equivalence relation, Granular computing, Computer science, Binary number, Dominance-based rough set approach, Relation (database)