Abstract
Based on lower and upper approximations induced by multiple binary relations, multigranulation rough set theory has become one of the most promising research topics in the domain of rough set theory. Through combining multigranulation rough sets with hesitant fuzzy linguistic term sets, this article introduces a hybrid model of multigranulation rough sets, named a hesitant fuzzy linguistic (HFL) multigranulation rough set. In the framework of granular computing, we first give basic definitions of optimistic and pessimistic hesitant fuzzy linguistic multigranulation rough sets. Then, we explore some important properties about hesitant fuzzy linguistic multigranulation rough sets. Lastly, uncertainty measures for the hesitant fuzzy linguistic multigranulation approximation space are addressed.
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Acknowledgments
The work was supported from the National Natural Science Foundation of China (No. 61272095, 61303107, 61432011, 61573231, U1435212) and the Shanxi Science and Technology Infrastructure (No. 2015091001-0102).
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Zhang, C., Li, DY., Zhai, YH. (2016). Multigranulation Rough Sets in Hesitant Fuzzy Linguistic Information Systems. In: Flores, V., et al. Rough Sets. IJCRS 2016. Lecture Notes in Computer Science(), vol 9920. Springer, Cham. https://doi.org/10.1007/978-3-319-47160-0_28
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DOI: https://doi.org/10.1007/978-3-319-47160-0_28
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