Forecasting of the COVID-19 Spreading in Global Using the Exponential Smoothing Method

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摘要
The World Health Organization (WHO) informed a cluster of cases of pneumonia of unknown cause detected in Wuhan City, Hubei Province of China on 31 December 2019. From this time, the disease had spread outside China, reaching countries in all parts of the globe. In this research, we conducted experiments to predict COVID-19 epidemic states using Holt’s linear trend of exponential smoothing method. In experiments, we used epidemiological data contains confirmed cases, deaths, and recovered cases from 22 January 2020 to 24 July 2020. In our experimental result, the Holt’s linear trend of exponential smoothing method shows about 1% errors in the average compared to the last 17 days of actual cases. According to this result, where the current situation would not change, in the third quarter of 2021, the number of confirmed cases is forecasted to reach 100 million, and deaths reach 3 million.
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关键词
COVID-19, Holt’s linear trend, Exponential smoothing method, Machine learning
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