Investigating the COVID19 Characteristics of the Countries Based on Time Series Clustering
Abstract
Keywords
References
- [1] Imtyaz A, Haleem A, Javaid M, Analysing Governmental Response to The COVID19 Pandemic, Journal of Oral Biology and Craniofacial Research, 10 (2020) 504-513.
- [2] Zarikas V, Poulopous SG, Gareiou Z, Zervas E, Clustering Analysis of the Countries COVID19 Data Sets, Data in Brief, (2020) 31.
- [3] Mahmoudi MR, Baleanu D, Mansor Z, Tuan BA, Pho K, Fuzzy Clustering Method to Compare The Spread Rate of COVID19 in The High-risk Countries, Chaos, Solitions and Fractals, (2020) 140.
- [4] Alvarez E, Brida JG, Limas E, Comparisions of COVID19 dynamics in the different countries of the World using time series clustering, (2020), medRxiv.
- [5] Hutagalung J, Ginantra NLWSR, Bhawika GW, Parwita WGS, Wanto A, Panjaitan PD. COVID19 Cases and Deaths in Southeast Asia Clustering Using K-means Clustering, Annual Conference on Science and Technology Research, Journal of Physics: Conference Series, (2021) 1783.
- [6] Virgantari F, Faridhan YE. K-means clustering of COVID19 cases in Indonesia’s provinces, Proceedings of the International Conference on Global Optimization and Its Applications, Jakarta, Indonesia, November 21-22, (2020).
- [7] Rojas F, Valenzuela O, Rojas I,. Estimation of COVID19 dynamics in the different states of the United States using time series clustering, (2020), medRxiv.
- [8] Azarafza M, Azarafza M, Akgün H, Clustering Method for Spread Pattern Analysis of Corona-virus (COVID19) Infection in Iran, Journal of Applied Science, Engineering, Technology, and Education, 3(1) (2021).
Details
Primary Language
English
Subjects
Statistics
Journal Section
Research Article
Authors
Öznur İşçi Güneri
0000-0003-3677-7121
Türkiye
Publication Date
March 30, 2022
Submission Date
July 10, 2021
Acceptance Date
March 5, 2022
Published in Issue
Year 2022 Volume: 43 Number: 1