Covering-Based generalized rough fuzzy sets

  • Authors:

  • Tao Feng;Jusheng Mi;Weizhi Wu

  • Affiliations:

  • College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, Hebei, P.R. China;College of Mathematics and Information Science, Hebei Normal University, Shijiazhuang, Hebei, P.R. China;Information College, Zhejiang Ocean University, Zhoushan, Zhejiang, P.R. China

  • Venue:
  • RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
  • Year:
  • 2006

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Abstract

This paper presents a general framework for the study of covering-based rough fuzzy sets in which a fuzzy set can be approximated by some elements in a covering of the universe of discourse. Some basic properties of the covering-based lower and upper approximation operators are examined. The concept of reduction of a covering is also introduced. By employing the discrimination matric of the covering, we provide an approach to find the reduct of a covering of the universe. It is proved that the reduct of a covering is the minimal covering that generates the same covering-based fuzzy lower (or upper) approximation operator, so this concept is also a technique to get rid of redundancy in data mining. Furthermore, it is shown that the covering-based fuzzy lower and upper approximations determine each other