Investigating the COVID19 Characteristics of the Countries Based on Time Series Clustering

npj Clean Water

article

Muhammet Oğuzhan YALÇIN¹  Nevin GÜLER DİNCER²  Öznur İŞÇİ GÜNERݲ 

[1] Mugla Sitki Kocman University Faculty of Science;MUĞLA SITKI KOÇMAN ÜNİVERSİTESİ

关键词: Fuzzy K-medois;    Cluster validity;    Time series clustering;    COVID19;   

DOI  :  10.17776/csj.969445

学科分类：社会科学、人文和艺术（综合）

来源: Springer

【 摘 要 】

The objective of this study is to reveal the COVID19 characteristics of the countries by using time seriesclustering. Up to now, various studies have been conducted for similar objectives. But, it has been observed thatthese studies belong to early time of pandemic and are involved limited number of countries. To analyze thecharacteristic of COVID19 more, this study has considered 111 countries and time period between the 4th ofApril 2020 and the 1st of January 2021. Fuzzy K-Medoid (FKM) is preferred as clustering method due to its threeabilities: i) FKM enables to determine the similarities and differences between the countries in more detail byutilizing the membership degrees, ii) In FKM, cluster centers are selected among from objects in the data set.Thus, it has the ability of detecting the countries which represent the behavior of all countries, iii) FKM is a robustmethod against to outliers. Thanks to this ability, FKM prevents that the countries exhibiting abnormal behaviornegatively affect to the clustering results. At the results of the analyses, it is observed that 111 countries havethree different behaviors in terms of confirmed cases and five different behaviors in terms of deaths.

【 授权许可】

CC BY