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Title: A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance
Authors: Thien, Nguyen Van
Demetrovics, Janos
Thi, Vu Duc
Giang, Nguyen Long
Son, Nguyen Nhu
Keywords: Granular Computing
Fuzzy Granular Structure
Fuzzy Information Granule
Fuzzy Information Granularity
Fuzzy Distance
Issue Date: 2016
Publisher: Institute of Mathematics and Informatics Bulgarian Academy of Sciences
Citation: Serdica Journal of Computing, Vol. 10, No 1, (2016), 013p-030p
Abstract: In fuzzy granular computing, a fuzzy granular structure is the collection of fuzzy information granules and fuzzy information granularity is used to measure the granulation degree of a fuzzy granular structure. In general, the fuzzy information granularity characterizes discernibility ability among fuzzy information granules in a fuzzy granular structure. In recent years, researchers have proposed some concepts of fuzzy information granularity based on partial order relations. However, the existing forms of fuzzy information granularity have some limitations when evaluating the fineness/coarseness between two fuzzy granular structures. In this paper, we propose an extension of fuzzy information granularity based on a fuzzy distance measure. We prove theoretically and experimentally that the proposed fuzzy information granularity is the best one to distinguish fuzzy granular structures. ACM Computing Classification System (1998): I.5.2, I.2.6.
ISSN: 1312-6555
Appears in Collections:Volume 10 Number 1

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