MADM Technique Using Tangent Trigonometric SvNN Aggregation Operators for the Teaching Quality Assessment of Teachers
| Autor: | Mailing Zhao, Jun Ye |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: | |
| Zdroj: | Neutrosophic Sets and Systems, Vol 50, Pp 651-662 (2022) |
| Druh dokumentu: | article |
| ISSN: | 2331-6055 2331-608X |
| DOI: | 10.5281/zenodo.6774966 |
| Popis: | In current Chinese higher education, the teaching quality assessment (TQA) of teachers in colleges/universities is an essential way to promotes the improvement of teacher teaching quality in the teaching process. In the TQA process of teachers, the evaluation information of experts/decision makers implies incompleteness, uncertainty and inconsistency corresponding to experts' cognition and judgment on evaluation indicators. Neutrosophic multiple attribute decision making (MADM) is one of key research topics in indeterminate and inconsistent decision-making problems. This paper presents a novel MADM technique using tangent trigonometric aggregation operators for single-valued neutrosophic numbers (SvNNs) to assess the teaching quality of teachers. First, we propose novel operational laws of tangent trigonometric SvNNs based on tangent trigonometric function. In view of the tangent trigonometric SvNN operational laws, we present tangent trigonometric SvNN weighted averaging and geometric operators to aggregate tangent trigonometric SvNNs. Then, we establish the MADM technique using the proposed two aggregation operators to perform MADM problems, and provide an actual example about the TQA of teachers and the comparison of existing related MADM techniques in the SvNN environment to reveal the efficiency and suitability of the proposed technique. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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