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Uncertainty Measures in Interval-Valued Information Systems

  • Nan ZhangEmail author
  • Zehua Zhang
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8818)

Abstract

Rough set theory is a new mathematical tool to deal with vagueness and uncertainty in artificial intelligence. Approximation accuracy, knowledge granularity and entropy theory are three main approaches to uncertainty research in classical Pawlak information system, which have been widely applied in many practical issues. Based on uncertainty measures in Pawlak information systems, we propose rough degree, knowledge discernibility and rough entropy in interval-valued information systems, and investigate some important properties of them. Finally, the relationships between knowledge granulation, knowledge discerniblity and rough degree have been also discussed.

Keywords

Upper and lower approximations rough sets uncertainty measures 

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Copyright information

© Springer International Publishing Switzerland 2014

Authors and Affiliations

  1. 1.School of Computer and Control EngineeringYantai UniversityYantaiChina
  2. 2.College of Computer Science and TechnologyTaiyuan University of TechnologyTaiyuanChina

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