Scopus Eşleşmesi Bulundu
27
Cilt
987-1001
Sayfa
🔓
Açık Erişim
Scopus Yazarları: Hakan Serin, M. K. Korez, Mehmet Emin Tekin, Sinan Siren
Özet
The biggest threat to the forests, which are natural habitats in European countries, as they are in the whole world, is forest fires. The aim of this study is to group the 38 European countries which have completely accessible fire indexes between the years 2008 to 2022; with respect to their similarities in fire regimes; and to compare the obtained groups with respect to their fire indexes. The clustering technique, which is a data mining method, was used while making these comparisons since it would be more objective and realistic to group and evaluate the countries according to their similarities. In the K-Means technique 2 clusters, and in the Ward's method 3 clusters were obtained. In the K-Means technique, significant statistical differences were found between the 2 clusters in terms of all fire indexes (p<0.05). In the Ward’s method, statistically significant differences were found between the clusters in terms of the number of fires, total area burned (ha) and woodland (p<0.05). In the result of the studies, the fire regimes in Turkey, Bosnia and Herzegovina, Ukraine, Italy, Spain, and Portugal resulted higher than the other countries in both clustering algorithms. Since many factors were taken into consideration in the study, countries heavily associated with fires such as Greece and France were separated from those with high fire regimes. It is recommended to conduct modelling studies with data mining algorithms by taking different fire indexes into account in order to increase the reliability of the results.
Anahtar Kelimeler (Scopus)
cluster analysis
Data mining method
forest fire
k-means
ward method
Scimago Dergi Bilgisi
Otomatik ISSN Eşleştirmesi
2023 yılı verileri
Sakarya University Journal of Science
-
SJR Quartile
8
H-Index
🔓
Açık Erişim
Kategoriler: Atomic and Molecular Physics, and Optics · Nuclear and High Energy Physics
Alanlar: Physics and Astronomy
Ülke: Turkey
· Sakarya University
Bu bilgiler makale yılına göre Scimago veritabanından ISSN eşleştirmesiyle otomatik getirilmektedir.
Dergi sıralama verileri Scimago'nun ilgili yılı baz alınmaktadır.
Anahtar Kelimeler
cluster analysis
Data mining method
forest fire
k-means
ward method
Makale Bilgileri
Dergi
Sakarya University Journal of Science
ISSN
2147-835X
Yıl
2023
/ 10. ay
Cilt / Sayı
27
/ 5
Sayfalar
987 – 1001
Makale Türü
Özgün Makale
Hakemlik
Hakemli
Endeks
TR DİZİN
TEŞV Puanı
2025,00
Yayın Dili
İngilizce
Kapsam
Ulusal
Toplam Yazar
4 kişi
Erişim Türü
Basılı+Elektronik
Erişim Linki
Makaleye Git
Alan
Fen Bilimleri ve Matematik Temel Alanı
İstatistik
YÖKSİS Yazar Kaydı
Yazar Adı
SERİN HAKAN, KÖREZ MUSLU KAZIM, TEKİN MEHMET EMİN, SİREN SİNAN
YÖKSİS ID
7677717
Hızlı Erişim
Metrikler
TEŞV Puanı
2025,00
Yazar Sayısı
4