Computer Science ›› 2018, Vol. 45 ›› Issue (10): 11-20.doi: 10.11896/j.issn.1002-137X.2018.10.003

• CGCKD 2018 • Previous Articles     Next Articles

Dynamic Parallel Updating Algorithm for Approximate Sets of Graded Multi-granulation Rough Set Based on Weighting Granulations and Dominance Relation

ZHAO Yi-lin1, JIANG Lin1, MI Yun-long2, LI Jin-hai1,3   

  1. Faculty of Science,Kunming University of Science and Technology,Kunming 650500,China 1
    School of Computer and Control Engineering,University of Chinese Academy of Sciences,Beijing 101408,China 2
    Data Science Research Center,Kunming University of Science and Technology,Kunming 650500,China 3
  • Received:2018-04-17 Online:2018-11-05 Published:2018-11-05

Abstract: With the continuous updating of large data sets,the classical multi-granulation rough set theory is no longer practical.Therefore,this paper put forward the related theory of graded pessimistic multi-granulation rough set with weighting granulations and dominance relation,graded optimistic multi-granulation rough set with weighting granulations and dominance relation.On the basis of this improved theory,this paper proposed a dynamic parallel updating algorithm forapproximate sets of graded multi-granulation rough set based on weighting granulations and dominance relation.Finally,the experiment verifies the effectiveness of the proposed algorithm,which is able to handle data with massive dynamic updates and improve running efficiency.

Key words: Multi-granulation rough set, Weighting, Dominance relation, Parallel updating algorithm

CLC Number: 

  • TP182
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