CANLI
Yükleniyor Veriler getiriliyor…
TR DİZİN Özgün Makale Scopus
Classification of Forest Fires in European Countries by Clustering Analysis Techniques
Sakarya University Journal of Science 2023 Cilt 27 Sayı 5
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