Information Entropy and Information Granulation-based Uncertainty Measures in Incomplete Information Systems

Authors

Lin Sun, College of Computer and Information Engineering, Henan Normal University, 453007 Xinxiang, China\\ Engineering Technology Research Center for Computing Intelligence and Data Mining, Henan Province, China\\ International WIC Institute, Beijing University of Technology, 100124 Beijing, ChinaFollow
Jiucheng Xu
Tianhe Xu

Author Country (or Countries)

China

Abstract

In this paper, concepts of information entropy and information granulation-based uncertainty measures are introduced in incomplete information/decision systems, and based on maximal consistent block technique, some variants of information entropy and information granulation are presented to measure the discernibility ability of an incomplete information system. Then, some important properties of them are discussed. From these properties, it can be shown that these proposed measures provide important approaches to measure the uncertainty ability of different knowledge in incomplete information/decision systems. And relationships among these measures are established as well. These results will be very helpful for understanding the essence of knowledge content and uncertainty measures in incomplete information systems.

Suggested Reviewers

N/A

Digital Object Identifier (DOI)

http://dx.doi.org/10.12785/amis/080466

Recommended Citation

Sun, Lin; Xu, Jiucheng; and Xu, Tianhe (2014) "Information Entropy and Information Granulation-based Uncertainty Measures in Incomplete Information Systems," Applied Mathematics & Information Sciences: Vol. 08: Iss. 4, Article 66.
DOI: http://dx.doi.org/10.12785/amis/080466
Available at: https://digitalcommons.aaru.edu.jo/amis/vol08/iss4/66