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.contributor.authorDinçer, Hasan
dc.contributor.authorPamucar, Dragan
dc.contributor.authorYüksel, Serhat
dc.contributor.authorDeveci, Muhammet
dc.contributor.authorEti, Serkan
dc.contributor.authorHacıoğlu, Ümit
dc.date.accessioned2025-06-03T07:21:53Z
dc.date.available2025-06-03T07:21:53Z
dc.date.issued2024
dc.departmentİstanbul Medipol Üniversitesi, İşletme ve Yönetim Bilimleri Fakültesi, Uluslararası Ticaret ve Finansman Bölümü
dc.departmentİstanbul Medipol Üniversitesi, İMÜ Meslek Yüksekokulu, Bilgisayar Programcılığı Ana Bilim Dalı
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, 23. http://dx.doi.org/10.1016/j.rineng.2024.102806
dc.identifier.doi10.1016/j.rineng.2024.102806
dc.identifier.issn2590-1230
dc.identifier.scopus2-s2.0-85202708532
dc.identifier.scopusqualityQ1
dc.identifier.urihttp://dx.doi.org/10.1016/j.rineng.2024.102806
dc.identifier.urihttps://hdl.handle.net/20.500.12511/12929
dc.identifier.volume23
dc.indekslendigikaynakScopus
dc.institutionauthorDinçer, Hasan
dc.institutionauthorYüksel, Serhat
dc.institutionauthorEti, Serkan
dc.institutionauthorid0000-0002-8072-031X
dc.institutionauthorid0000-0002-9858-1266
dc.institutionauthorid0000-0002-4791-4091
dc.language.isoen
dc.relation.ispartofResults in Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.rightsAttribution-NonCommercial 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/
dc.subjectArtificial Intelligence
dc.subjectEnergy Technology
dc.subjectEnergy Transition
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

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