Uncertainty Measures of Roughness of Knowledge and Rough Sets in Ordered Information Systems

  • Authors:

  • Wei-Hua Xu;Hong-Zhi Yang;Wen-Xiu Zhang

  • Affiliations:

  • Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, Shaan'xi 710049, P.R. China;He'nan Pingyuan University, Xinxiang 453003, P.R. China, Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, Shaan'xi 710049, P.R. China;Faculty of Science, Institute for Information and System Sciences, Xi'an Jiaotong University, Xi'an, Shaan'xi 710049, P.R. China

  • Venue:
  • ICIC '07 Proceedings of the 3rd International Conference on Intelligent Computing: Advanced Intelligent Computing Theories and Applications. With Aspects of Artificial Intelligence
  • Year:
  • 2009

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Abstract

Rough set theory has been considered as a useful tool to deal with inexact, uncertain, or vague knowledge. However, in real-world, most of information systems are based on dominance relations, called ordered information systems, in stead of the classical equivalence for various factors. So, it is necessary to find a new measure to knowledge and rough set in ordered information systems. In this paper, we address uncertainty measures of roughness of knowledge and rough sets by introducing rough entropy in ordered information systems. We prove that the rough entropy of knowledge and rough set decreases monotonously as the granularity of information becomes finer, and obtain some conclusions, which is every helpful in future research works of ordered information systems.