On knowledge reduction in inconsistent decision information systems

  • Authors:

  • Deyu Li;Bo Zhang;Yee Leung

  • Affiliations:

  • State Key Laboratory of Intelligent Technology and Systems, Dept. of Comp. Sci. and Technol., Tsinghua Univ., Beijing 100084 and Inst. of Comp. Appl., Dept. of Comp. Sci., Shanxi Univ., Taiyuan, S ...;State Key Laboratory of Intelligent Technology and Systems, Department of Computer Science and Technology, Tsinghua University, Beijing 100084, People's Republic of China;Centre for Environmental Policy and Resource Management and Joint Laboratory for Geoinformation Science, The Chinese University of Hong Kong, Hong Kong

  • Venue:
  • International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
  • Year:
  • 2005

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Abstract

Due to issues such as noise in data, compact representation and prediction capability, many types of knowledge reduction and decision rules have been proposed and applied in inconsistent decision information systems. It is thus important to clarify the interrelationships among the existing types of knowledge reduction. In this paper, the relationships, particularly those suggested in [1], are reconsidered and rectified, and some related results are theoretically improved. In terms of two new types of reducts proposed in this paper together with other existing ones, the method for optimizing all types of decision rules is also discussed in details.