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The prediction and analysis of COVID-19 epidemic trend by combining LSTM and Markov method.
Ma, Ruifang; Zheng, Xinqi; Wang, Peipei; Liu, Haiyan; Zhang, Chunxiao.
  • Ma R; School of Information Engineering, China University of Geosciences, Beijing, China.
  • Zheng X; School of Information Engineering, China University of Geosciences, Beijing, China. zhengxq@cugb.edu.cn.
  • Wang P; Technology Innovation Center for Territory Spatial Big-Data, MNR of China, Beijing, China. zhengxq@cugb.edu.cn.
  • Liu H; School of Information Engineering, China University of Geosciences, Beijing, China. peipeiwang@cugb.edu.cn.
  • Zhang C; School of Economic and Management, China University of Geosciences, Beijing, 100083, China.
Sci Rep ; 11(1): 17421, 2021 08 31.
Article in English | MEDLINE | ID: covidwho-1380913
ABSTRACT
Corona Virus Disease 2019 (COVID-19) has spread rapidly to countries all around the world from the end of 2019, which caused a great impact on global health and has had a huge impact on many countries. Since there is still no effective treatment, it is essential to making effective predictions for relevant departments to make responses and arrangements in advance. Under the limited data, the prediction error of LSTM model will increase over time, and its prone to big bias for medium- and long-term prediction. To overcome this problem, our study proposed a LSTM-Markov model, which uses Markov model to reduce the prediction error of LSTM model. Based on confirmed case data in the US, Britain, Brazil and Russia, we calculated the training errors of LSTM and constructed the probability transfer matrix of the Markov model by the errors. And finally, the prediction results were obtained by combining the output data of LSTM model with the prediction errors of Markov Model. The results show that compared with the prediction results of the classical LSTM model, the average prediction error of LSTM-Markov is reduced by more than 75%, and the RMSE is reduced by more than 60%, the mean [Formula see text] of LSTM-Markov is over 0.96. All those indicators demonstrate that the prediction accuracy of proposed LSTM-Markov model is higher than that of the LSTM model to reach more accurate prediction of COVID-19.
Subject(s)

Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America / South America / Asia / Brazil / Europa Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-97037-5

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Full text: Available Collection: International databases Database: MEDLINE Main subject: COVID-19 Type of study: Experimental Studies / Observational study / Prognostic study / Randomized controlled trials Limits: Humans Country/Region as subject: North America / South America / Asia / Brazil / Europa Language: English Journal: Sci Rep Year: 2021 Document Type: Article Affiliation country: S41598-021-97037-5