Holistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach

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dc.authorid0000-0002-8072-031X
dc.authorid0009-0003-5219-1283
dc.authorid0000-0002-4791-4091
dc.authorid0000-0002-0068-0048
dc.contributor.authorDinçer, Hasan
dc.contributor.authorPamucar, Dragan
dc.contributor.authorYüksel, Serhat
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorEti, Serkan
dc.contributor.authorHacıoğlu, Ümit
dc.contributor.otherYönetim Bilimleri Fakültesi, İşletme Bölümü
dc.date.accessioned2024-09-03T05:23:48Z
dc.date.available2024-09-03T05:23:48Z
dc.date.issued2024
dc.departmentİHÜ, Yönetim Bilimleri Fakültesi, İşletme Bölümü
dc.description.abstractThe most essential criteria should be determined in the selection of the suitable energy transition technologies due to budget deficit problem. Therefore, it is necessary to identify the most important criteria in energy transition technology selection. Therefore, a new study is needed to determine the most prominent issues in the correct selection of energy transition technologies. The purpose of this study is to identify the most appropriate energy transition technology alternative. Within this framework, a novel artificial intelligence (AI)-based fuzzy decision-making model has been presented. In the first part, the experts are prioritized by the help of AI methodology. In the next section, missing evaluations of energy transition technology investments are estimated via expert recommender system. Thirdly, the weights of the criteria for energy transition technology selection are computed by quantum picture fuzzy rough sets (QPFR) M-Stepwise Weight Assessment Ratio Analysis (SWARA). At the final stage, selected energy transition technology alternatives are ranked via QPFR-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR). The main contribution of this study is the integration of AI technique to the proposed model. Similar to this issue, using M-SWARA methodology in the process of criteria weighting increases the quality of the findings. This methodology helps to consider the impact relation map of the criteria. The findings demonstrate that the most important factor is cost-effectiveness of energy transition. Similarly, it is also found that the local ecosystem is the second most significant issue. On the other side, the ranking results denote that compact renewable systems for small scale production is the most optimal solution of energy transition technology alternatives.
dc.identifier.citationDinçer, H., Pamucar, D., Yüksel, S., Deveci, M., Eti, S. ve Hacıoğlu, Ü. (2024). Holistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach. Results in Engineering, 24, 1-18. https://www.doi.org/10.1016/j.rineng.2024.102806
dc.identifier.doi10.1016/j.rineng.2024.102806
dc.identifier.endpage18
dc.identifier.issn2590-1230
dc.identifier.scopus2-s2.0-85202708532
dc.identifier.scopusqualityQ1
dc.identifier.startpage1
dc.identifier.urihttps://www.doi.org/10.1016/j.rineng.2024.102806
dc.identifier.urihttps://hdl.handle.net/20.500.12154/2994
dc.identifier.volume23
dc.indekslendigikaynakScopus
dc.institutionauthorDinçer, Hasan
dc.institutionauthorid0000-0002-0068-0048
dc.institutionauthorid0000-0002-8072-031X
dc.language.isoen
dc.publisherElsevier
dc.relation.ispartofResults in Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.subjectEnergy Transition
dc.subjectEnergy Technology
dc.subjectArtificial Intelligence
dc.subjectFuzzy Decision-Making
dc.subjectRecommender System
dc.titleHolistic evaluation of energy transition technology investments using an integrated recommender system and artificial intelligence-based fuzzy decision-making approach
dc.typeArticle
dspace.entity.typePublication
relation.isAuthorOfPublicationd5642aa4-347e-4bbe-bcd5-6b4b19a4c49f
relation.isAuthorOfPublication.latestForDiscoveryd5642aa4-347e-4bbe-bcd5-6b4b19a4c49f
relation.isOrgUnitOfPublicationc9253b76-6094-4836-ac99-2fcd5392d68f
relation.isOrgUnitOfPublication.latestForDiscoveryc9253b76-6094-4836-ac99-2fcd5392d68f

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