Forecasting the Number of Coronavirus (COVID-19) Cases in Ethiopia Using Exponential Smoothing Times Series Model

T. Abebe
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引用次数: 5

Abstract

The main objective of this study is to forecast COVID-19 case in Ethiopiausing the best-fitted model. The time series data of COVID-19 case in Ethiopia from March 14, 2020 to June 05, 2020 were used.To this end, exponential growth, single exponential smoothing method, and doubleexponential smoothing methodwere used. To evaluate the forecasting performance of the model, root mean sum of square error was used. The study showed that double exponential smoothing methods was appropriate in forecasting the future number ofCOVID-19 cases in Ethiopia as dictated by lowest value of root mean sum of square error. The forecasting model shows that the number of coronavirus cases in Ethiopia grows exponentially. The finding of the results would help the concerned stakeholders to make the right decisions based on the information given on forecasts.
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利用指数平滑时间序列模型预测埃塞俄比亚新冠肺炎病例数
本研究的主要目的是使用最佳拟合模型预测埃塞俄比亚的COVID-19病例。使用埃塞俄比亚2020年3月14日至2020年6月05日COVID-19病例时间序列数据。为此,采用了指数增长法、单指数平滑法和双指数平滑法。为了评估模型的预测性能,使用均方根误差和。研究表明,双指数平滑法适用于预测埃塞俄比亚未来新冠肺炎病例数,因为其均方根误差最小。预测模型显示,埃塞俄比亚的冠状病毒病例数呈指数级增长。结果的发现将有助于有关的利益相关者根据预测提供的信息做出正确的决策。
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