A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance
Serdica Journal of Computing, Tome 10 (2016) no. 1, pp. 013-030.

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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.
Keywords: Granular Computing, Fuzzy Granular Structure, Fuzzy Information Granule, Fuzzy Information Granularity, Fuzzy Distance
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Thien, Nguyen Van; Demetrovics, Janos; Thi, Vu Duc; Giang, Nguyen Long; Son, Nguyen Nhu. A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance. Serdica Journal of Computing, Tome 10 (2016) no. 1, pp. 013-030. http://geodesic.mathdoc.fr/item/SJC_2016_10_1_a1/