| Autor: |
Abrar Hussain, Kifayat Ullah, Sman Almas, Sarbast Moslem, Tapan Senapati |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
|
| Zdroj: |
IEEE Access, Vol 12, Pp 124095-124110 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
2169-3536 |
| DOI: |
10.1109/ACCESS.2024.3453115 |
| Popis: |
The multi-attribute group decision-making (MAGDM) technique is a potent approach used to evaluate an appropriate optimal option under the system of various characteristics or attributes information. The aggregation operators (AOs) play a significant role in the aggregation process and fuse a large amount of uncertain information into a single set. In this article, dominant terminologies of t-spherical fuzzy sets apply to handle vague and ambiguous information related to human opinion. Some flexible operations of Einstein operations are also modified in the light of t-spherical fuzzy information. The power operators characterized relationships among various types of preference information. Keeping in mind the significance of discussed terminologies, we developed some Einstein mathematical approaches, including T-SF Einstein power-weighted average (T-SFEPWA) and T-SF Einstein power-weighted geometric (T-SFEPWG) operators. Some desirable characteristics and special cases are also demonstrated to reveal the reliability of developed approaches. An algorithm for the MAGDM problem is also established to resolve different real-life situations. To show the consistency and effectiveness of the proposed approaches, the author illustrates a numerical example to choose an appropriate data analysis tool under the system of T-SF information. Additionally, a comprehensive comparison method verifies the validity and feasibility of diagnosed mathematical approaches with existing AOs in the literature. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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