Utilize este identificador para referenciar este registo: http://hdl.handle.net/10071/28849
Registo completo
Campo DCValorIdioma
dc.contributor.authorZhytkevych, O.-
dc.contributor.authorBrochado, A.-
dc.date.accessioned2023-06-30T15:43:54Z-
dc.date.available2023-06-30T15:43:54Z-
dc.date.issued2022-
dc.identifier.citationZhytkevych, O., & Brochado, A. (2022). Modeling national decarbonization capabilities using Kohonen maps. Neuro-Fuzzy Modeling Techniques in Economics, 11, 3-24. https://dx.doi.org/10.33111/nfmte.2022.003-
dc.identifier.issn2415-3516-
dc.identifier.urihttp://hdl.handle.net/10071/28849-
dc.description.abstractThis study sought to develop a method to cluster countries based on their decarbonization capabilities and to determine how these nations’ reduction of carbon dioxide (CO2) emissions has evolved over time. CO2 emissions clusters were identified using 11 indicators that measure both direct and indirect CO2 emissions, differentiating countries by their economic and population growth, energy consumption, and CO2 emission level. The panel data included 39 countries over the 10-year period of 2012–2021. The clustering was based on such type of neural networks as Kohonen self-organizing maps. This type of model facilitated grouping countries by similar decarbonization capabilities and economic development. The findings reveal that Norway and Sweden are the leaders in creating climate-resilient economies among the 39 countries analyzed. The analysis carried out can help other countries establish benchmarks for improving their own internal decarbonization activities based on leader nations’ strategies and borrowing their best practices for more efficient results. This study thus contributes to the literature regarding decarbonization activities by offering a multi-country dynamic clustering method using Kohonen maps.eng
dc.language.isoeng-
dc.publisherKyiv National Economic University-
dc.rightsopenAccess-
dc.subjectCarbon dioxide (CO2)eng
dc.subjectEmission targeteng
dc.subjectDecarbonizationeng
dc.subjectClusteringeng
dc.subjectSelf-organizingmapeng
dc.subjectNeural networkeng
dc.titleModeling national decarbonization capabilities using Kohonen mapseng
dc.typearticle-
dc.pagination3 - 24-
dc.peerreviewedyes-
dc.number11-
dc.date.updated2023-06-30T16:43:22Z-
dc.description.versioninfo:eu-repo/semantics/publishedVersion-
dc.identifier.doi10.33111/nfmte.2022.003-
iscte.identifier.cienciahttps://ciencia.iscte-iul.pt/id/ci-pub-96157-
iscte.alternateIdentifiers.scopus2-s2.0-85160745947-
iscte.journalNeuro-Fuzzy Modeling Techniques in Economics-
Aparece nas coleções:DINÂMIA'CET-RI - Artigos em revistas internacionais com arbitragem científica

Ficheiros deste registo:
Ficheiro TamanhoFormato 
article_96157.pdf1,4 MBAdobe PDFVer/Abrir


FacebookTwitterDeliciousLinkedInDiggGoogle BookmarksMySpaceOrkut
Formato BibTex mendeley Endnote Logotipo do DeGóis Logotipo do Orcid 

Todos os registos no repositório estão protegidos por leis de copyright, com todos os direitos reservados.