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Knowledge Reduction in Random Incomplete Information Systems via Evidence Theory

  • Wei-Zhi Wu
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6401)

Abstract

Knowledge reduction is one of the main problems in the study of rough set theory. This paper deals with knowledge reduction in random incomplete information systems based on Dempster-Shafer theory of evidence. The concepts of random belief reducts and random plausibility reducts in random incomplete information systems are introduced. The relationships among the random belief reduct, the random plausibility reduct, and the classical reduct are examined. It is proved that, in a random incomplete information system, an attribute set is a random belief reduct if and only if it is a classical reduct, and a random plausibility consistent set must be a consistent set.

Keywords

Belief functions incomplete information systems knowledge reduction random incomplete information systems rough sets 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Wei-Zhi Wu
    • 1
  1. 1.School of Mathematics, Physics and Information ScienceZhejiang Ocean University, ZhoushanZhejiangP.R. China

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