Unifying Variable Precision and Classical Rough Sets: Granular Approach

Part of the Intelligent Systems Reference Library book series (ISRL, volume 43)

Abstract

The primary goal of this paper is to show that neighborhood systems (NS) can integrate Ziarko’s variable precision and Pawlak ’s classical rough sets into one concept. NS was introduced by T.Y. Lin in 1989 to capture the concepts of “near” (in generalized topology) and “conflicts” (studied using non-reflexive and symmetric binary relation). Currently, NS’s are widely used in granular computing.

Keywords

Rough sets granular computing variable precision rough set model (VPRS) neighborhood systems binary neighborhood systems 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  1. 1.Department of Computer ScienceSan Jose State UniversitySan JoseUSA
  2. 2.Department of Information ManagementNational Formosa UniversityHuweiTaiwan

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