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A new extension of hesitant fuzzy set: An application to an offshore wind turbine technology selection process

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dc.contributor.author Narayanamoorthy, Samayan
dc.contributor.author Ramya, Lakshmanaraj
dc.contributor.author Kang, Daekook
dc.contributor.author Baleanu, Dumitru
dc.contributor.author Kureethara, Joseph Varghese
dc.contributor.author Annapoorani, Veerappan
dc.date.accessioned 2022-02-24T07:15:52Z
dc.date.available 2022-02-24T07:15:52Z
dc.date.issued 2021-08
dc.identifier.citation Narayanamoorthy, Samayan...et al. (2021). "A new extension of hesitant fuzzy set: An application to an offshore wind turbine technology selection process", IET Renewable Power Generation, Vol. 15, No. 11, pp. 2340-2355. tr_TR
dc.identifier.issn 1752-1424
dc.identifier.uri http://hdl.handle.net/20.500.12416/5048
dc.description.abstract Wind energy is an energy source that is naturally clean, safe and cheap. It comes from a variety of sources. The electric energy generated by a wind turbine manifests as kinetic energy throughout the earth. The energy received from the wind is clean and is permanently available and can be generated forever. Turbine characteristics also have an impact on wind energy production. The turbine properties within a wind farm are important in estimating the load on power generation and wind turbine energy. The amount of energy released is calculated according to the type of the turbine model applied. In many situations, the choices of turbine model can incur various vague and complicated hesitation situations. To manage this situation, a hesitant fuzzy set with the Multi Criteria Decision Making (MCDM) is used. In the present research, the newly proposed Normal Wiggly Hesitant Fuzzy-Criteria Importance Through Intercriteria Correlation (NWHF-CRITIC) and Normal Wiggly Hesitant Fuzzy-Multi Attribute Utility Theory (NWHF-MAUT) methods were employed to rank turbine models based on quality, power level, voltage, and capacity. As part of this process, the NWHF method was utilized to extract and gather deeper information from the decision-makers. tr_TR
dc.language.iso eng tr_TR
dc.relation.isversionof 10.1049/rpg2.12168 tr_TR
dc.rights info:eu-repo/semantics/openAccess tr_TR
dc.title A new extension of hesitant fuzzy set: An application to an offshore wind turbine technology selection process tr_TR
dc.type article tr_TR
dc.relation.journal IET Renewable Power Generation tr_TR
dc.contributor.authorID 56389 tr_TR
dc.identifier.volume 15 tr_TR
dc.identifier.issue 11 tr_TR
dc.identifier.startpage 2340 tr_TR
dc.identifier.endpage 2355 tr_TR
dc.contributor.department Çankaya Üniversitesi, Fen - Edebiyat Fakültesi, Matematik Bölümü tr_TR


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