Exploring T-spherical fuzzy sets for enhanced evaluation of vocal music classroom teaching

Author:

Lu Yani

Abstract

Vocal music is a relatively complex skill and skill course, which not only plays an important role in music education in universities, but also cultivates students’ musical level and artistic cultivation. In the process of teaching vocal music in universities, how to improve the quality of teaching has become an important task and goal for teachers. The vocal music classroom teaching quality evaluation is a classical multiple-attribute group decision-making (MAGDM) problem. In this paper, some novel Dice similarity measures (DSM) and some generalized Dice similarity measures (GDSM) are proposed under T-spherical fuzzy sets (T-SFSs). Then, the weighted generalized Dice similarity measures (WGDSM) is used to solve the MAGDM with T-SFSs. Finally, an illustrative example for vocal music classroom teaching quality evaluation is given to demonstrate the efficiency of the GDSMs.

Publisher

IOS Press

Subject

Artificial Intelligence,Control and Systems Engineering,Software

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