Adjustable Multigranulation SVN Probabilistic Rough Sets With Application to Teamwork Evaluations

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.