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Uncertainty measure for general relation-based rough fuzzy set

Sun Bingzhen (School of Economics & Management, Tongji University, Shanghai, China and School of Traffic and Transportation, Lanzhou Jiaotong University, Lanzhoui, China)
Ma Weimin (School of Economic and Management, Tongji University, Shanghai, China)

Kybernetes

ISSN: 0368-492X

Article publication date: 24 June 2013

422

Abstract

Purpose

The purpose of this paper is to present a measure method of the uncertainty for rough fuzzy set based on general binary relation.

Design/methodology/approach

Rough set and fuzzy set are two different but complementary theories for expressing uncertainty information, and based on the combination of these two uncertainty theories of expressing and handling uncertainty information, the rough fuzzy set model and uncertainty measure based on general relation are discussed.

Findings

This paper reveals the intrinsic of the uncertainty for rough fuzzy set based on general relation and presents a new measure method by introducing the Shannon entropy to generalized approximation space.

Originality/value

The paper contributes to the discussion on the research of rough set and fuzzy set. The conclusions are useful in information processing with uncertainty.

Keywords

Acknowledgements

The work was partly supported by the National Natural Science Foundation of China (71161016, 71071113). The Fundamental Research Funds for the Central Universities.

Citation

Bingzhen, S. and Weimin, M. (2013), "Uncertainty measure for general relation-based rough fuzzy set", Kybernetes, Vol. 42 No. 6, pp. 979-992. https://doi.org/10.1108/K-12-2012-0119

Publisher

:

Emerald Group Publishing Limited

Copyright © 2013, Emerald Group Publishing Limited

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