Hakan SERİN, Muslu Kazım KÖREZ, Mehmet Emin TEKİN, Sinan SİREN
{"title":"基于聚类分析技术的欧洲国家森林火灾分类","authors":"Hakan SERİN, Muslu Kazım KÖREZ, Mehmet Emin TEKİN, Sinan SİREN","doi":"10.16984/saufenbilder.1288073","DOIUrl":null,"url":null,"abstract":"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","PeriodicalId":21468,"journal":{"name":"Sakarya University Journal of Science","volume":"25 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-06-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Classification of Forest Fires in European Countries by Clustering Analysis Techniques\",\"authors\":\"Hakan SERİN, Muslu Kazım KÖREZ, Mehmet Emin TEKİN, Sinan SİREN\",\"doi\":\"10.16984/saufenbilder.1288073\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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\",\"PeriodicalId\":21468,\"journal\":{\"name\":\"Sakarya University Journal of Science\",\"volume\":\"25 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-06-21\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Sakarya University Journal of Science\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.16984/saufenbilder.1288073\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sakarya University Journal of Science","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.16984/saufenbilder.1288073","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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