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10.3390/ijerph17124582 http://scihub22266oqcxt.onion/10.3390/ijerph17124582 32630565!7344860!32630565     free     free     free Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 217.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Int+J+Environ+Res+Public+Health 2020 ; 17 (12): ä Nephropedia Template TP {{tp|p=32630565|t=2020. Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models |pdf=|usr=}}{{32630565}} gab.com Text Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models JO: Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32630565 #FOAvip The outbreak of a novel coronavirus (SARS-CoV-2) has caused a large number of residents in China to be infected with a highly contagious pneumonia recently. Despite active control measures taken by the Chinese government, the number of infected patients is still increasing day by day. At present, the changing trend of the epidemic is attracting the attention of everyone. Based on data from 21 January to 20 February 2020, six rolling grey Verhulst models were built using 7-, 8- and 9-day data sequences to predict the daily growth trend of the number of patients confirmed with COVID-19 infection in China. The results show that these six models consistently predict the S-shaped change characteristics of the cumulative number of confirmed patients, and the daily growth decreased day by day after 4 February. The predicted results obtained by different models are very approximate, with very high prediction accuracy. In the training stage, the maximum and minimum mean absolute percentage errors (MAPEs) are 4.74% and 1.80%, respectively; in the testing stage, the maximum and minimum MAPEs are 4.72% and 1.65%, respectively. This indicates that the predicted results show high robustness. If the number of clinically diagnosed cases in Wuhan City, Hubei Province, China, where COVID-19 was first detected, is not counted from 12 February, the cumulative number of confirmed COVID-19 cases in China will reach a maximum of 60,364-61,327 during 17-22 March; otherwise, the cumulative number of confirmed cases in China will be 78,817-79,780. Twit Text FOAVip Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models ????Int J Environ Res Public Health http://www.kidney.de/pget.php?&tw=1&pmid=32630565 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=32630565 #FOAvip English Wikipedia <ref>{{Cite pmid|32630565}}</ref> Prediction of the Number of Patients Infected with COVID-19 Based on Rolling Grey Verhulst Models #MMPMID32630565 Zhao YF; Shou MH; Wang ZX Int J Environ Res Public Health 2020[Jun]; 17 (12): ä PMID32630565show ga The outbreak of a novel coronavirus (SARS-CoV-2) has caused a large number of residents in China to be infected with a highly contagious pneumonia recently. Despite active control measures taken by the Chinese government, the number of infected patients is still increasing day by day. At present, the changing trend of the epidemic is attracting the attention of everyone. Based on data from 21 January to 20 February 2020, six rolling grey Verhulst models were built using 7-, 8- and 9-day data sequences to predict the daily growth trend of the number of patients confirmed with COVID-19 infection in China. The results show that these six models consistently predict the S-shaped change characteristics of the cumulative number of confirmed patients, and the daily growth decreased day by day after 4 February. The predicted results obtained by different models are very approximate, with very high prediction accuracy. In the training stage, the maximum and minimum mean absolute percentage errors (MAPEs) are 4.74% and 1.80%, respectively; in the testing stage, the maximum and minimum MAPEs are 4.72% and 1.65%, respectively. This indicates that the predicted results show high robustness. If the number of clinically diagnosed cases in Wuhan City, Hubei Province, China, where COVID-19 was first detected, is not counted from 12 February, the cumulative number of confirmed COVID-19 cases in China will reach a maximum of 60,364-61,327 during 17-22 March; otherwise, the cumulative number of confirmed cases in China will be 78,817-79,780. |Betacoronavirus/isolation & purification[MESH] |COVID-19[MESH] |China/epidemiology[MESH] |Coronavirus Infections/*epidemiology/virology[MESH] |Humans[MESH] |Models, Statistical[MESH] |Pandemics/*statistics & numerical data[MESH] |Pneumonia, Viral/*epidemiology/virology[MESH]Prediction of the Number of Patients Infected with COVID-19 Based on R(epmc).pdf DeepDyve Pubget Overpricing