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Article type: Research Article
Authors: Zhang, Haidonga; * | He, Yanpingb | Ma, Weiyuana
Affiliations: [a] School of Mathematics and Computer Science, Northwest MinZu University, Lanzhou, Gansu, P. R. China | [b] School of Electrical Engineering, Northwest MinZu University, Lanzhou, Gansu, P. R. China
Correspondence: [*] Corresponding author. Haidong Zhang, School of Mathematics and Computer Science, Northwest MinZu University, Lanzhou, Gansu, P. R. China. Tel./Fax: +86 9314512202; E-mails: [email protected].
Abstract: Through a combination of hesitant fuzzy sets with rough sets, this study develops a single-granulation hesitant fuzzy rough set model from the perspective of granular computing. In the multi-granulation framework, we propose two types of multi-granulation rough set model, called the optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets. In the models, the multi-granulation hesitant fuzzy lower and upper approximations are defined based on multiple hesitant fuzzy tolerance relations. The relationships among the single-granulation hesitant fuzzy rough sets, optimistic multi-granulation hesitant fuzzy rough sets and pessimistic multi-granulation hesitant fuzzy rough sets are also investigated. Finally, we develop an approximation reduction approach of multi-granulation hesitant fuzzy rough sets to eliminate redundant hesitant fuzzy granulations with a detailed example.
Keywords: Single-granulation hesitant fuzzy rough set, Multi-granulation hesitant fuzzy rough set, Hesitant fuzzy granulations, Approximation reduction
DOI: 10.3233/JIFS-18586
Journal: Journal of Intelligent & Fuzzy Systems, vol. 37, no. 1, pp. 1555-1567, 2019
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