DSpace Repository

Extension of Einstein Average Aggregation Operators to Medical Diagnostic Approach Under q-Rung Orthopair Fuzzy Soft Se

Show simple item record

dc.contributor.author Zulqarnain, Rana Muhammad
dc.contributor.author Rehman, Hafiz Khalil Ur
dc.contributor.author Awrejcewicz, Jan
dc.contributor.author Ali, Rifaqat
dc.contributor.author Siddique, Imran
dc.contributor.author Jarad, Fahd
dc.contributor.author Iampan, Aiyared
dc.date.accessioned 2024-03-21T12:53:06Z
dc.date.available 2024-03-21T12:53:06Z
dc.date.issued 2022
dc.identifier.citation Zulqarnain, Rana Muhammad;...et.al. (2022). "Extension of Einstein Average Aggregation Operators to Medical Diagnostic Approach Under q-Rung Orthopair Fuzzy Soft Set", IEEE Access, Vol.10, pp.87923-87949. tr_TR
dc.identifier.issn 21693536
dc.identifier.uri http://hdl.handle.net/20.500.12416/7688
dc.description.abstract The paradigm of the soft set (SS) was pioneered by Moldotsov in 1999 by prefixing the parametrization tool in accustomed sets, which yields general anatomy in decision-making (DM) problems. The q-rung orthopair fuzzy soft set (q-ROFSS) is an induced form of the intuitionistic fuzzy soft set (IFSS) and Pythagorean fuzzy soft set (PFSS). It is also a more significant structure to tackle complex and vague information in DM problems than IFSS and PFSS. This manuscript explores new notions based on Einstein's operational laws for q-rung orthopair fuzzy soft numbers (q-ROFSNs). Our main contribution is to investigate some average aggregation operators (AOs), such as q-rung orthopair fuzzy soft Einstein weighted average (q-ROFSEWA) and q-rung orthopair fuzzy soft Einstein ordered weighted average (q-ROFSEOWA) operators. Besides, the fundamental axioms of proposed operators are discussed. Multi-criteria group decision-making (MCGDM) is vigorous in dealing with the compactness of real-world obstacles, and still, the prevailing MCGDM methods constantly convey conflicting consequences. Based on offered AOs, a robust MCGDM approach is deliberated to accommodate the defects of the prevalent MCGDM methodologies under the q-ROFSS setting. Based on the planned MCGDM method, a medical diagnostic procedure is implemented to recognize the nature of certain infections in different patients. The protracted model estimates illustrious score values to determine patients' health compared to prevailing models, which is more helpful for healthcare experts in identifying the severity of diseases in patients. Furthermore, an inclusive comparative analysis is accomplished to ratify the pragmatism and effectiveness of the proposed technique with some formerly standing methods. The consequences gained over comparative studies display that our established method is more proficient than predominant methodologies. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1109/ACCESS.2022.3199069 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject MCGDM tr_TR
dc.subject Q-ROFSEOWA Operator tr_TR
dc.subject Q-ROFSEWA Operator tr_TR
dc.subject Q-Rung Orthopair Fuzzy Soft Set tr_TR
dc.title Extension of Einstein Average Aggregation Operators to Medical Diagnostic Approach Under q-Rung Orthopair Fuzzy Soft Se tr_TR
dc.type article tr_TR
dc.relation.journal IEEE Access tr_TR
dc.contributor.authorID 234808 tr_TR
dc.identifier.volume 10 tr_TR
dc.identifier.startpage 87923 tr_TR
dc.identifier.endpage 87949 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen-Edebiyat Fakültesi, Matematik Bölümü tr_TR


Files in this item

Files Size Format View

There are no files associated with this item.

This item appears in the following Collection(s)

Show simple item record