基于聚类分析技术的欧洲国家森林火灾分类

Hakan SERİN, Muslu Kazım KÖREZ, Mehmet Emin TEKİN, Sinan SİREN
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引用次数: 0

摘要

森林既是欧洲国家的自然栖息地,也是全世界的自然栖息地,对森林最大的威胁是森林火灾。本研究的目的是对2008年至2022年间具有完全可访问的火灾指数的38个欧洲国家进行分组;关于他们在火灾制度方面的相似性;并比较得到的基团的火灾指数。在进行这些比较时使用了聚类技术,这是一种数据挖掘方法,因为根据相似性对国家进行分组和评估将更加客观和现实。k -均值法得到2个聚类,Ward法得到3个聚类。在K-Means技术中,2个聚类之间在所有5个指数方面存在显著的统计学差异(p
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Classification of Forest Fires in European Countries by Clustering Analysis Techniques
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
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