A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance

Thien, Nguyen Van, et al. "A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance." Serdica Journal of Computing 10.1 (2016): 013-030. <http://eudml.org/doc/289527>.

@article{Thien2016,
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.},
author = {Thien, Nguyen Van, Demetrovics, Janos, Thi, Vu Duc, Giang, Nguyen Long, Son, Nguyen Nhu},
journal = {Serdica Journal of Computing},
keywords = {Granular Computing; Fuzzy Granular Structure; Fuzzy Information Granule; Fuzzy Information Granularity; Fuzzy Distance},
language = {eng},
number = {1},
pages = {013-030},
publisher = {Institute of Mathematics and Informatics Bulgarian Academy of Sciences},
title = {A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance},
url = {http://eudml.org/doc/289527},
volume = {10},
year = {2016},
}

TY - JOUR
AU - Thien, Nguyen Van
AU - Demetrovics, Janos
AU - Thi, Vu Duc
AU - Giang, Nguyen Long
AU - Son, Nguyen Nhu
TI - A Method to Construct an Extension of Fuzzy Information Granularity Based on Fuzzy Distance
JO - Serdica Journal of Computing
PY - 2016
PB - Institute of Mathematics and Informatics Bulgarian Academy of Sciences
VL - 10
IS - 1
SP - 013
EP - 030
AB - 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.
LA - eng
KW - Granular Computing; Fuzzy Granular Structure; Fuzzy Information Granule; Fuzzy Information Granularity; Fuzzy Distance
UR - http://eudml.org/doc/289527
ER -