Attribute reduction in incomplete information systems

  • Authors:

  • Shibao Sun;Jianhui Duan;Dandan Wanyan

  • Affiliations:

  • Electronic Information Engineering College, Henan University of Science and Technology, Luoyang Henan, China and National Laboratory Of Software Development Environment, Beijing University of Aero ...;Electronic Information Engineering College, Henan University of Science and Technology, Luoyang Henan, China;Electronic Information Engineering College, Henan University of Science and Technology, Luoyang Henan, China

  • Venue:
  • AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
  • Year:
  • 2011

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Abstract

Through changing the equivalence relation of objects to reflexive and symmetric binary relation in the incomplete information system, a cumulative variable precision rough set model is proposed. The basic properties of β lower and β upper cumulative approximation operators are investigated. β upper, and β lower distribution consistent set are explored for defining β upper, and β lower distribution cumulative reduction. Finally, two attribute reduction approaches, such as β upper (β lower) distribution cumulative reduction, in the incomplete information system are given through discernible matrix and function. The example proves that the cumulative variable precision rough set model can effectively deal with information and fully maintain knowledge in incomplete information systems.