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Application of improved fuzzy best worst analytic hierarchy process on renewable energy

In this work, a novel fuzzy decision making technique namely trapezoidal fuzzy Best-Worst method (fuzzy BWM) is developed which is based on Best-Worst method (BWM) and Trapezoidal fuzzy number. The real motive behind our work is to take a broad view of the existing fuzzy BWM based on triangular fuzz...

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Autores principales: Majumder, Priyanka, Balas, Valentina Emilia, Paul, Arnab, Baidya, Dayarnab
Formato: Online Artículo Texto
Lenguaje:English
Publicado: PeerJ Inc. 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053020/
https://www.ncbi.nlm.nih.gov/pubmed/33954237
http://dx.doi.org/10.7717/peerj-cs.453
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author Majumder, Priyanka
Balas, Valentina Emilia
Paul, Arnab
Baidya, Dayarnab
author_facet Majumder, Priyanka
Balas, Valentina Emilia
Paul, Arnab
Baidya, Dayarnab
author_sort Majumder, Priyanka
collection PubMed
description In this work, a novel fuzzy decision making technique namely trapezoidal fuzzy Best-Worst method (fuzzy BWM) is developed which is based on Best-Worst method (BWM) and Trapezoidal fuzzy number. The real motive behind our work is to take a broad view of the existing fuzzy BWM based on triangular fuzzy number by trapezoidal fuzzy number. Also, we have presented a new hybrid MCDM technique called as Trapezoidal fuzzy Best Worst Analytic Hierarchy based on proposed trapezoidal fuzzy BWM and existing trapezoidal fuzzy Analytic Hierarchy Process (AHP). BWM approach is employed in evaluating the PV of considering criteria and trapezoidal fuzzy AHP is used to assess the local priority vale (PV) of considering alternatives (or indicators) of a decision problem. Moreover it used to identify the most significant alternative which is responsible for performance efficiency of a hydro power plant under climatic scenario. From the result, it is undoubtedly found that hydraulic had is most responsible indicator. Further, the CR (consistency ratio) value which is determined by our proposed trapezoidal fuzzy BWM is less than that of existing BWM and fuzzy BWM techniques. Finally, we have validated our result by comparative study, scenario analysis and sensitivity analysis.
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spelling pubmed-80530202021-05-04 Application of improved fuzzy best worst analytic hierarchy process on renewable energy Majumder, Priyanka Balas, Valentina Emilia Paul, Arnab Baidya, Dayarnab PeerJ Comput Sci Artificial Intelligence In this work, a novel fuzzy decision making technique namely trapezoidal fuzzy Best-Worst method (fuzzy BWM) is developed which is based on Best-Worst method (BWM) and Trapezoidal fuzzy number. The real motive behind our work is to take a broad view of the existing fuzzy BWM based on triangular fuzzy number by trapezoidal fuzzy number. Also, we have presented a new hybrid MCDM technique called as Trapezoidal fuzzy Best Worst Analytic Hierarchy based on proposed trapezoidal fuzzy BWM and existing trapezoidal fuzzy Analytic Hierarchy Process (AHP). BWM approach is employed in evaluating the PV of considering criteria and trapezoidal fuzzy AHP is used to assess the local priority vale (PV) of considering alternatives (or indicators) of a decision problem. Moreover it used to identify the most significant alternative which is responsible for performance efficiency of a hydro power plant under climatic scenario. From the result, it is undoubtedly found that hydraulic had is most responsible indicator. Further, the CR (consistency ratio) value which is determined by our proposed trapezoidal fuzzy BWM is less than that of existing BWM and fuzzy BWM techniques. Finally, we have validated our result by comparative study, scenario analysis and sensitivity analysis. PeerJ Inc. 2021-04-13 /pmc/articles/PMC8053020/ /pubmed/33954237 http://dx.doi.org/10.7717/peerj-cs.453 Text en © 2021 Majumder et al. https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, reproduction and adaptation in any medium and for any purpose provided that it is properly attributed. For attribution, the original author(s), title, publication source (PeerJ Computer Science) and either DOI or URL of the article must be cited.
spellingShingle Artificial Intelligence
Majumder, Priyanka
Balas, Valentina Emilia
Paul, Arnab
Baidya, Dayarnab
Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title_full Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title_fullStr Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title_full_unstemmed Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title_short Application of improved fuzzy best worst analytic hierarchy process on renewable energy
title_sort application of improved fuzzy best worst analytic hierarchy process on renewable energy
topic Artificial Intelligence
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8053020/
https://www.ncbi.nlm.nih.gov/pubmed/33954237
http://dx.doi.org/10.7717/peerj-cs.453
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