Clustering of the Black Sea Region meteorological stations of Türkiye with fuzzy c-means, k-means, and silhouette index analysis methods by precipitation, temperature and wind speed

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dc.contributor.authorKeskin, Asli Ulke
dc.contributor.authorKir, Gurkan
dc.contributor.authorZeybekoglu, Utku
dc.date.accessioned2026-04-25T14:20:25Z
dc.date.available2026-04-25T14:20:25Z
dc.date.issued2025
dc.departmentSinop Üniversitesi
dc.description.abstractRecent years have seen a marked increase in the number of disasters caused by the effects of global climate change. In response, a range of studies have been conducted in T & uuml;rkiye and worldwide with the aim of reducing the impact of climate change.The classification of regions affected by climate change into similar classes in terms of climate parameters is crucial for the application of consistent methods in studies conducted in these regions. Consequently, the formulation of effective strategies to mitigate the repercussions of climate change in these regions is contingent upon the accurate determination of the aforementioned strategy.The observation records evaluated within the scope of the study were obtained from 31 stations of the Turkish State Meteorological Service in the Black Sea Region, encompassing the period between 1982 and 2020, encompassing precipitation, temperature, and wind speed records.. The maximum number of clusters was determined as 5, the cluster analysis study was carried out by using fuzzy c-means and k-means methods for 2, 3, 4, and 5 cluster numbers according to these three data together form a matrix. The determination of the optimum cluster numbers was carried out by silhouette index analysis. For the data matrix where precipitation, temperature, and wind speed were evaluated together, the most appropriate classification was obtained by the k-means method by choosing the number of clusters as 4.
dc.identifier.doi10.28974/idojaras.2025.1.6
dc.identifier.issn0324-6329
dc.identifier.issue1
dc.identifier.scopus2-s2.0-105000568648
dc.identifier.scopusqualityQ4
dc.identifier.urihttps://doi.org/10.28974/idojaras.2025.1.6
dc.identifier.urihttps://hdl.handle.net/11486/8555
dc.identifier.volume129
dc.identifier.wosWOS:001449563000006
dc.identifier.wosqualityQ4
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherHungarian Meteorological Service
dc.relation.ispartofIdojaras
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/openAccess
dc.snmzKA_WOS_20260420
dc.subjectcluster analysis
dc.subjectsilhouette index analysis
dc.subjectwind speed
dc.subjectprecipitation
dc.subjecttemperature
dc.subjectfuzzy c-means
dc.subjectk-means
dc.titleClustering of the Black Sea Region meteorological stations of Türkiye with fuzzy c-means, k-means, and silhouette index analysis methods by precipitation, temperature and wind speed
dc.typeArticle

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