UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS-Reference-Cited by-同舟云学术

UNCERTAINTY MEASURE OF ROUGH SETS BASED ON A KNOWLEDGE GRANULATION FOR INCOMPLETE INFORMATION SYSTEMS

Published:2008-04 Issue:02 Volume:16 Page:233-244
ISSN:0218-4885
Container-title:International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
language:en
Short-container-title:Int. J. Unc. Fuzz. Knowl. Based Syst.

Author:

WANG JUNHONG¹,LIANG JIYE¹,QIAN YUHUA¹,DANG CHUANGYIN²

Affiliation:

1. Key Laboratory of Ministry of Education for Computational Intelligence and Chinese Information Processing, School of Computer and Information Technology, Shanxi University, Taiyuan 030006, China

2. Department of Manufacturing Engineering and Engineering Management, City University of Hong Kong, 83 Tat Chee Avenue, Kowloon, Hong Kong

Abstract

Rough set theory is a relatively new mathematical tool for computer applications in circumstances characterized by vagueness and uncertainty. In this paper, we address uncertainty of rough sets for incomplete information systems. An axiom definition of knowledge granulation for incomplete information systems is obtained, under which a measure of uncertainty of a rough set is proposed. This measure has some nice properties such as equivalence, maximum and minimum. Furthermore, we prove that the uncertainty measure is effective and suitable for measuring roughness and accuracy of rough sets for incomplete information systems.

Publisher

World Scientific Pub Co Pte Lt

Subject

Artificial Intelligence,Information Systems,Control and Systems Engineering,Software

Link

https://www.worldscientific.com/doi/pdf/10.1142/S0218488508005157

Reference15 articles.

1. Rough Sets

2. An approach for constructing complex discriminating surfaces based on Bayesian interference of the maximum entropy

3. Uncertainty measures of rough set prediction

4. Uncertainty-Based Information

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