Affiliations: [a] Department of Mathematics, Riphah International University (Lahore Campus), Islamabad, Pakistan
| [b] Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa, Saudi Arabia
| [c] School of Mathematics, Thapar Institute of Engineering & Technology (Deemed University) Patiala, Punjab, India
| [d] Department of Mathematics, Graphic Era Deemed to be University, Dehradun, Uttarakhand, India
| [e] Applied Science Research Center, Applied Science Private University, Amman, Jordan
| [f] College of Technical Engineering, Department of Medical Devices Engineering Technologies, National University of Science and Technology, Dhi Qar, Nasiriyah, Iraq
Correspondence:
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Corresponding author. Kifayat Ullah, Department of Mathematics, Riphah International University Lahore, (Lahore Campus) 54000, Lahore Pakistan. E-mail: [email protected] and Ashraf Al-Quran, Basic Sciences Department, Preparatory Year Deanship, King Faisal University, Al-Ahsa 31982, Saudi Arabia. E-mail: [email protected].
Abstract: Renewable energy sources play an influential role in the world’s climate and reduce the rate of harmful gasses such as carbon dioxide, methane, nitrous oxide, and many other greenhouse gasses that contribute to global warming. The theoretical concept of the T-spherical fuzzy (T-SF) set (T-SFS) is the most suitable model to evaluate energy resources under uncertainty. This article illustrates appropriate operations based on Dombi triangular norm and t-conorm. We derived a series of new aggregation approaches, such as T-SF Dombi Hamy mean (T-SFDHM) and T-SF weighted Dombi Hamy Mean (T-SFDWHM) operators. Further authors illustrated a list of new approaches such as T-SF Dual Dombi Hamy mean (T-SFDDHM), and T-SF Dombi weighted Dual Hamy mean (T-SFDWDHM) operators. Some exceptional cases and desirable properties of our derived approaches are also studied. We illustrate an application of renewable energy resources to be evaluated using a multi-attribute group decision-making (MAGDM) method. A case study was also studied to choose appropriate energy resources using our proposed methodology of the T-SFDWHM and T-SFDWDHM operators. To show the effectiveness and validity of our current methods, we compared the existing results with currently developed aggregation operators (AOs).
