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Prediction of the confirmed cases and deaths of global COVID-19 using artificial intelligence

文献类型：期刊论文

作者Guo, Qingchun1,2; He, Zhenfang1,3
刊名ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
出版日期2021-01-07
页码11
关键词SARS-CoV-2 COVID-19 Epidemic Infected cases Deaths Artificial intelligence
ISSN号0944-1344
DOI10.1007/s11356-020-11930-6
通讯作者Guo, Qingchun(guoqingchun@lcu.edu.cn) ; He, Zhenfang(hezhenfang@lcu.edu.cn)
英文摘要The outbreak of coronavirus disease 2019 (COVID-19) has seriously affected the environment, ecology, economy, society, and human health. With the global epidemic dynamics becoming more and more serious, the prediction and analysis of the confirmed cases and deaths of COVID-19 has become an important task. We develop an artificial neural network (ANN) for modeling of the confirmed cases and deaths of COVID-19. The confirmed cases and deaths data are collected from January 20 to November 11, 2020 by the World Health Organization (WHO). By introducing root mean square error (RMSE), correlation coefficient (R), and mean absolute error (MAE), statistical indicators of the prediction model are verified and evaluated. The size of training and test confirmed cases and death base employed in the model is optimized. The best simulating performance with RMSE, R, and MAE is realized using the 7 past days' cases as input variables in the training and test dataset. And the estimated R are 0.9948 and 0.9683, respectively. Compared with different algorithms, experimental simulation shows that trainbr algorithm has better performance than other algorithms in reproducing the amount of the confirmed cases and deaths. This study shows that the ANN model is suitable for predicting the confirmed cases and deaths of COVID-19 in the future. Using the ANN model, we also predict the confirmed cases and deaths of COVID-19 from June 5, 2020 to November 11, 2020. During the predicting period, the R, RMSE, and MAE for new infected confirmed cases of COVID-19 are 0.9848, 17,554, and 12,229, respectively; the R, RMSE, and MAE for new confirmed deaths of COVID-19 are 0.8593, 631.8, and 463.7, respectively. The predicted confirmed cases and deaths of COVID-19 are very close to the actual confirmed cases and deaths. The results show that continuous and strict control measures should be taken to prevent the further spread of the epidemic.
WOS关键词NEURAL-NETWORKS ; CORONAVIRUS ; CHINA
资助项目National Natural Science Fund of China[41572150] ; National Natural Science Fund of China[41472162] ; National Natural Science Fund of China[41702373] ; Shandong Social Sciences Planning Research Fund[18CKPJ34] ; Shandong Province Higher Educational Humanities and Social Science Fund[J18RA196] ; State Key Laboratory of Loess and Quaternary Geology Found[SKLLQG1907]
WOS研究方向Environmental Sciences & Ecology
语种英语
WOS记录号WOS:000607363600019
出版者SPRINGER HEIDELBERG
资助机构National Natural Science Fund of China ; Shandong Social Sciences Planning Research Fund ; Shandong Province Higher Educational Humanities and Social Science Fund ; State Key Laboratory of Loess and Quaternary Geology Found
源URL[http://ir.ieecas.cn/handle/361006/15842]  
专题地球环境研究所_黄土与第四纪地质国家重点实验室（2010~）
通讯作者Guo, Qingchun; He, Zhenfang
作者单位1.Liaocheng Univ, Sch Environm & Planning, Liaocheng 252000, Shandong, Peoples R China
2.Chinese Acad Sci, Inst Earth Environm, State Key Lab Loess & Quaternary Geol, Xian 710061, Peoples R China
3.Chinese Acad Sci, Res Ctr Ecoenvironm Sci, State Key Lab Urban & Reg Ecol, Beijing 100085, Peoples R China
推荐引用方式
GB/T 7714		 Guo, Qingchun,He, Zhenfang. Prediction of the confirmed cases and deaths of global COVID-19 using artificial intelligence[J]. ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,2021:11.
APA Guo, Qingchun,&He, Zhenfang.(2021).Prediction of the confirmed cases and deaths of global COVID-19 using artificial intelligence.ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH,11.
MLA Guo, Qingchun,et al."Prediction of the confirmed cases and deaths of global COVID-19 using artificial intelligence".ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH (2021):11.

入库方式： OAI收割

来源：地球环境研究所

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