Financial multidimensional assessment of a green hydrogen generation process via an integrated artificial intelligence-based four-stage fuzzy decision-making model

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dc.authorid0000-0002-9858-1266
dc.authorid0000-0002-8072-031X
dc.authorid0000-0001-5853-4943
dc.authorid0000-0003-2212-287X
dc.authorid0000-0002-4791-4091
dc.authorid0000-0002-3390-4597
dc.contributor.authorYüksel, Serhat
dc.contributor.authorDinçer, Hasan
dc.contributor.authorAcar, Merve
dc.contributor.authorErgün, Edanur
dc.contributor.authorEti, Serkan
dc.contributor.authorGökalp, Yaşar
dc.date.accessioned2024-10-30T07:00:10Z
dc.date.available2024-10-30T07:00:10Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, İMÜ Meslek Yüksekokulu, Bilgisayar Programcılığı Ana Bilim Dalı
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
dc.departmentİstanbul Medipol Üniversitesi, Sağlık Bilimleri Fakültesi, Sağlık Yönetimi Bölümü
dc.description.abstractIt is widely accepted that there is an urgent need to make green hydrogen (GH2) projects financially viable to reduce global warming. However, any form of improvements to these GH2 projects lead to substantial cost increase. Due to this cost increase, making many improvements negatively affects the financial profitability of hydrogen projects. This is why there is a need for new advanced financial priority analysis tools so that it is easier to develop GH2 projects globally. Accordingly, the aim of this study is to identify and then define the most important factors affecting GH2 generation projects. To achieve this aim, this work proposes a new fuzzy multi-criteria decision-making model based on artificial intelligence (AI). First, experts are weighted with AI technique. Second, the missing evaluations are filled via a recommender system. Third, criteria weights are calculated by the M-SWARA technique integrated with quantum picture fuzzy rough (QPFR) sets. Finally, GH2 energy generation processes are listed by the QPFR-VIKOR approach. Overall, the main contribution of this study is the generation of a comprehensive AI oriented fuzzy decision-making model to make a detailed evaluation with respect to the financial potential improvements of the GH2 generation projects. The main originality of this model is the consideration of AI to calculate the weights of the criteria. Similarly, another benefit of the proposed model, that increases its superiority against other models, is the completion of missing evaluations by experts thanks to the recommender system. It is concluded that the most important criterion affecting green hydrogen investments is organizational effectiveness.
dc.identifier.citationYüksel, S., Dinçer, H., Acar, M., Ergün, E., Eti, S. ve Gökalp, Y. (2024). Financial multidimensional assessment of a green hydrogen generation process via an integrated artificial intelligence-based four-stage fuzzy decision-making model. International Journal of Hydrogen Energy, 83, 577-588. http://dx.doi.org/10.1016/j.ijhydene.2024.08.140
dc.identifier.doi10.1016/j.ijhydene.2024.08.140
dc.identifier.endpage588
dc.identifier.issn0360-3199
dc.identifier.issn1879-3487
dc.identifier.scopus2-s2.0-85201115431
dc.identifier.scopusqualityQ1
dc.identifier.startpage577
dc.identifier.urihttp://dx.doi.org/10.1016/j.ijhydene.2024.08.140
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12838
dc.identifier.volume83
dc.identifier.wos001295849200001en_US
dc.identifier.wosqualityQ1
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.institutionauthorYüksel, Serhat
dc.institutionauthorDinçer, Hasan
dc.institutionauthorAcar, Merve
dc.institutionauthorErgün, Edanur
dc.institutionauthorEti, Serkan
dc.institutionauthorGökalp, Yaşar
dc.language.isoen
dc.relation.ispartofInternational Journal of Hydrogen Energyen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectArtificial Intelligence
dc.subjectClean Energy
dc.subjectFuzzy Decision-Making
dc.subjectGreen Hydrogen
dc.subjectHydrogen Generation
dc.titleFinancial multidimensional assessment of a green hydrogen generation process via an integrated artificial intelligence-based four-stage fuzzy decision-making model
dc.typeArticle

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