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Adjustable Multigranulation SVN Probabilistic Rough Sets With Application to Teamwork Evaluations
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Author(s): Wenhui Bai (Shanxi University, China), Juanjuan Ding (Shanxi University, China), Chao Zhang (Shanxi University, China), Yanhui Zhai (Shanxi University, China), Deyu Li (Shanxi University, China)and Said Broumi (Laboratory of Information Processing, Faculty of Science Ben M'Sik, University Hassan II, Casablanca, Morocco & Regional Center for the Professions of Education and Training (CRMEF), Morocco)
Copyright: 2023
Pages: 22
Source title:
Handbook of Research on the Applications of Neutrosophic Sets Theory and Their Extensions in Education
Source Author(s)/Editor(s): Said Broumi (Laboratory of Information Processing, Faculty of Science Ben M’Sik, University of Hassan II, Casablanca, Morocco & Regional Center for the Professions of Education and Training (CRMEF), Morocco)
DOI: 10.4018/978-1-6684-7836-3.ch002
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Abstract
In the community of generalized fuzzy sets, the notion of single-valued neutrosophic sets (SVNSs) enables individuals to express their preferences by processing the indeterminate information, thus it plays a significant role in intelligent information processing. For addressing teamwork assessment tasks in the education setting, this chapter concentrates on exploring a viable teamwork assessment method via multi-attribute group decision-making (MAGDM). After revisiting basic notions of SVNSs and multigranulation probabilistic rough sets (MG PRSs), this chapter first puts forth a new model named adjustable multigranulation (MG) single-valued neutrosophic (SVN) probabilistic rough sets (PRSs), which integrates the advantages of SVNSs in information descriptions and multi-granularity computing in information fusion. Then in the setting of teamwork assessments, this chapter constructs a valid MAGDM method by means of adjustable MG SVN PRSs and decision-theoretic rough sets (DTRSs). Finally, a case study analysis is conducted by virtue of a UCI data set in the education setting.
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