Knowledge reduction in random information systems via Dempster-Shafer theory of evidence

  • Authors:

  • Wei-Zhi Wu;Mei Zhang;Huai-Zu Li;Ju-Sheng Mi

  • Affiliations:

  • Information College, Zhejiang Ocean University, Zhejiang, PR China;National Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaan'xi, PR China and School of Management, Xi'an Jiaotong University, Xi'an, Shaan'xi, PR China;National Key Laboratory of Manufacturing Systems Engineering, Xi'an Jiaotong University, Xi'an, Shaan'xi, PR China and School of Management, Xi'an Jiaotong University, Xi'an, Shaan'xi, PR China;College of Mathematics and Information Sciences, Hebei Normal University, Hebei, PR China

  • Venue:
  • Information Sciences: an International Journal
  • Year:
  • 2005

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Abstract

Knowledge reduction is one of the main problems in the study of rough set theory. This paper deals with knowledge reduction in (random) information systems based on Dempster-Shafer theory of evidence. The concepts of belief and plausibility reducts in (random) information systems are first introduced. It is proved that both of belief reduct and plausibility reduct are equivalent to classical reduct in (random) information systems. The relative belief and plausibility reducts in consistent and inconsistent (random) decision systems are then proposed and compared to the relative reduct and relationships between the new reducts and some existing ones are examined.