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dc.contributor.authorSarikoc, Gulhan Ozdogan
dc.date.accessioned2025-03-28T07:23:05Z
dc.date.available2025-03-28T07:23:05Z
dc.date.issued2024
dc.identifier.issn0262-6667
dc.identifier.issn2150-3435
dc.identifier.urihttps://doi.org/10.1080/02626667.2024.2356006
dc.identifier.urihttps://hdl.handle.net/20.500.12450/6006
dc.description.abstractIn this study, a bibliometric analysis technique is used for performance analysis and science mapping of artificial intelligence (AI) applications in streamflow research. This paper examines the current trends in the literature using the Scopus database over the last 37 years. RStudio Bibliometrix software was used to analyse the titles, keywords, abstracts, and full texts of 3000 publications to identify trends in AI models, publication types, journals, citations, authors, countries, and regions. The highest frequency AI-related keyword is artificial neural networks, which was used in a total of 25587 times. The most common publication type, at 82.1%, is journal articles, and the highest rate of country production is 25% for China. In recent years, streamflow research studies have significantly increased their use of AI applications. [GRAPHICS] .en_US
dc.language.isoengen_US
dc.publisherTaylor & Francis Ltden_US
dc.relation.ispartofHydrological Sciences Journalen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial intelligenceen_US
dc.subjectstreamflowen_US
dc.subjectbibliometricen_US
dc.subjectresearch trendsen_US
dc.subjectScopusen_US
dc.subjectRStudio Bibliometrixen_US
dc.titleArtificial intelligence applications in the field of streamflow: a bibliometric analysis of recent trendsen_US
dc.typearticleen_US
dc.departmentAmasya Üniversitesien_US
dc.identifier.volume69en_US
dc.identifier.issue9en_US
dc.identifier.startpage1141en_US
dc.identifier.endpage1157en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.institutionauthorSarikoc, Gulhan Ozdogan
dc.identifier.scopus2-s2.0-85195265363en_US
dc.identifier.doi10.1080/02626667.2024.2356006
dc.department-temp[Sarikoc, Gulhan Ozdogan] Amasya Univ, Suluova Vocat Sch, Dept Vegetable & Anim Prod, Amasya, Turkiyeen_US
dc.identifier.wosWOS:001253039200001en_US
dc.snmzKA_WOS_20250328
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US


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