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The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location

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dc.contributor.author Narayanamoorthy, Samayan
dc.contributor.author Nallasivan Parthasarathy, Thirumalai
dc.contributor.author Pragathi, Subramaniam
dc.contributor.author Shanmugam, Ponnan
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Ahmadian, Ali
dc.contributor.author Kang, Daekook
dc.date.accessioned 2024-05-14T08:06:43Z
dc.date.available 2024-05-14T08:06:43Z
dc.date.issued 2022-10
dc.identifier.citation Narayanamoorthy, Samayan...et.al. (2022). "The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location", Sustainable Energy Technologies and Assessments, Vol.53, No.2. tr_TR
dc.identifier.issn 2213-1388
dc.identifier.uri http://hdl.handle.net/20.500.12416/8312
dc.description.abstract The Fermatean fuzzy set has been authorized as a suitable tool for the uncertainty and vagueness of information by augmenting the spatial space of acceptance membership and non-acceptance membership degrees of both intuitionistic and Pythagorean fuzzy sets. Solar energy does not emit any hazardous gases into the atmosphere, making it one of the most effective strategies to reduce global warming in the environment. Under a variety of circumstances, finding a spot for a photovoltaic solar power plant might be difficult. As a result, we experiment with multi-criteria decision-making (MCDM) techniques. We presented a hybrid technique based on the PV-SPSS method based on the Removal Effects of Criteria (MEREC) and Multiple Objective Optimization on the Basis of Ratio Analysis with Full Multiplicative Form (MULTIMOORA) analysis. The MEREC approach is used to calculate the weightage of each attribute, and MULTIMOORA is used to find the ranking of the alternatives. Also, a new rectified generalized score function determines the score value of FFSs. Culmination: the validity of the result is assessed by implementing the existing MCDM approaches and by changing the criterion weight. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1016/j.seta.2022.102488 tr_TR
dc.rights info:eu-repo/semantics/closedAccess tr_TR
dc.subject MCDM tr_TR
dc.subject Fermatean Fuzzy Set tr_TR
dc.subject MEREC tr_TR
dc.subject MULTIMOORA tr_TR
dc.subject PV-SPSS tr_TR
dc.title The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location tr_TR
dc.type article tr_TR
dc.relation.journal Sustainable Energy Technologies and Assessments tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 53 tr_TR
dc.identifier.issue 2 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen-Edebiyat Fakültesi, Matematik Bölümü tr_TR


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