Knowledge granulation, knowledge entropy and knowledge uncertainty measure in ordered information systems

  • Authors:

  • Xu Wei-hua;Zhang Xiao-yan;Zhang Wen-xiu

  • Affiliations:

  • School of Mathematics and Physics, Chongqing Institute of Technology, Chongqing 400054, China;School of Mathematics and Physics, Chongqing Institute of Technology, Chongqing 400054, China;School of Science, Xi'an Jiaotong University, Xi'an 710019, China

  • Venue:
  • Applied Soft Computing
  • Year:
  • 2009

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Abstract

In this paper, concepts of knowledge granulation, knowledge entropy and knowledge uncertainty measure are given in ordered information systems, and some important properties of them are investigated. From these properties, it can be shown that these measures provides important approaches to measuring the discernibility ability of different knowledge in ordered information systems. And relationship between knowledge granulation, knowledge entropy and knowledge uncertainty measure are considered. As an application of knowledge granulation, we introduce definition of rough entropy of rough sets in ordered information systems. By an example, it is shown that the rough entropy of rough sets is more accurate than classical rough degree to measure the roughness of rough sets in ordered information systems.