AN ESTIMATION OF NUMBER OF DAILY DEATHS DUE TO COVID-19 IN UNITED STATES OF AMERICA, UNITED KINGDOM AND TURKEY

Q4 Earth and Planetary Sciences ASEAN Engineering Journal Pub Date : 2023-02-28 DOI:10.11113/aej.v13.17713
E. Ülker, Sadik Ülker
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Abstract

Covid-19 virus is threatening the world with health, social and economic implications and all around the world data is obtained continuously with pandemic for modelling and predicting the future. In this work, support vector regression technique was used to make some predictions on the daily death values due to Covid-19 virus. The models were created for the world, United States of America, United Kingdom and Turkey. All the regression models were tested using coefficient of determination (R2) and root mean square error (RMSE) values. The analysis was also conducted for comparing the suitability of linear, radial and polynomial kernels. The radial kernel produced relatively better results. In predicting the world data support vector regression with radial kernel produced 0.805262 R2 value on test data. In the models created for United States of America 0.723376 R2 value, for United Kingdom 0.95412 R2 value and for Turkey 0.875343 R2 value using test data were observed. Also, while the models were created for specific countries the comparisons were made between using only data for the country and also using the whole world data. In general modelling using the data for the world combined with the country data gave better prediction.
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美国、英国和土耳其每日因新冠肺炎死亡人数的估计
新冠肺炎病毒正在威胁世界,对健康、社会和经济产生影响,世界各地的数据都是随着疫情不断获得的,用于建模和预测未来。在这项工作中,使用支持向量回归技术对新冠肺炎病毒导致的每日死亡值进行了一些预测。这些模型是为世界、美利坚合众国、英国和土耳其创建的。使用决定系数(R2)和均方根误差(RMSE)值对所有回归模型进行测试。还进行了分析,以比较线性、径向和多项式核的适用性。径向核产生了相对较好的结果。在预测世界数据时,径向核支持向量回归在测试数据上产生0.805262 R2值。在使用测试数据为美利坚合众国创建的模型中,观察到0.723376 R2值、英国0.95412 R2值和土耳其0.875343 R2值。此外,虽然这些模型是为特定国家创建的,但在仅使用该国的数据和使用整个世界的数据之间进行了比较。一般来说,使用世界数据和国家数据进行建模可以提供更好的预测。
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来源期刊
ASEAN Engineering Journal
ASEAN Engineering Journal Engineering-Engineering (all)
CiteScore
0.60
自引率
0.00%
发文量
75
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