Research on Uncertainty of Rough Fuzzy Sets in Different Knowledge Granularity Levels

Author

Zhang Qinghua

Author_Institution

Coll. of Math. & Phys., Chongqing Univ. of Posts & Telecommun., Chongqing, China

Volume

3

fYear

2010

fDate

11-12 May 2010

Firstpage

190

Lastpage

193

Abstract

The rough fuzzy sets (RFS) is a combination granular computing model with rough sets and fuzzy sets. Its uncertainty includes roughess, rough entropy, fuzziness and fuzzy entropy, etc.. In this paper, the changes of roughness, cut-set and fuzziness are discussed according to the knowledge granularity in different knowledge granularity levels in apporiximation spaces of rough fuzzy sets. Hence, the regularity of the uncertainty of rough fuzzy sets in different knowledge granularity levels is discovered, namely the roughness and fuzziness of rough fuzzy sets will decrease with the refinement of knowledge granularity in approximation spaces, and the cut-set of lower approximations will increase and the cut-set of upper approximations will decrease.

Keywords

fuzzy set theory; knowledge based systems; rough set theory; uncertainty handling; approximation cut set; approximation space; combination granular computing model; fuzzy entropy; knowledge granularity level; rough entropy; rough fuzzy set uncertainty; Automation; Entropy; Fuzzy control; Fuzzy set theory; Fuzzy sets; Fuzzy systems; Measurement uncertainty; Physics computing; Rough sets; Telecommunication computing; Cut-set; Fuzziness; Knowledge Granularity; Rough Fuzzy Sets; Roughness;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Computation Technology and Automation (ICICTA), 2010 International Conference on

Conference_Location

Changsha

Print_ISBN

978-1-4244-7279-6

Electronic_ISBN

978-1-4244-7280-2

Type

conf

DOI

10.1109/ICICTA.2010.683

Filename

5523271