Temporal deep learning architecture for prediction of COVID-19 cases in India

作者：

Highlights：

• Various variants of LSTM and CNN deep learning architectures have been designed.

• Predicted COVID-19 confirmed cases for India and its four most affected states.

• RMSE and MAPE are computed to compare the performance of the designed models.

• Experimental results show that predicted cases are very close to actual cases.

摘要

•Various variants of LSTM and CNN deep learning architectures have been designed.•Predicted COVID-19 confirmed cases for India and its four most affected states.•RMSE and MAPE are computed to compare the performance of the designed models.•Experimental results show that predicted cases are very close to actual cases.

论文关键词：Deep learning,COVID-19,CNN,LSTM

论文评审过程：Received 28 October 2021, Revised 9 January 2022, Accepted 22 January 2022, Available online 5 February 2022, Version of Record 10 February 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.116611