The novel augmented Fermatean MCDM perspectives for identifying the optimal renewable energy power plant location
Sustainable Energy Technologies and Assessments, ISSN: 2213-1388, Vol: 53, Page: 102488
2022
- 56Citations
- 50Captures
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
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Article Description
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.
Bibliographic Details
http://www.sciencedirect.com/science/article/pii/S2213138822005380; http://dx.doi.org/10.1016/j.seta.2022.102488; http://www.scopus.com/inward/record.url?partnerID=HzOxMe3b&scp=85134797894&origin=inward; https://linkinghub.elsevier.com/retrieve/pii/S2213138822005380; https://dx.doi.org/10.1016/j.seta.2022.102488
Elsevier BV
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