Forecasting of Novel Corona Cases in India Using LSTM-Based Recurrent Neural Networks

ABSTRACT

Novel corona disease is spreading all over the world. The cases of the corona virus are increasing drastically day by day. Therefore, it is necessary to predict the cases in advance to handle the condition. Recently, machine learning comes into the picture of researchers to solve the problem in engineering. The present study is focused to the application of LSTM recurrent neural network to predict the Novel corona cases on the daily basis in India. Various RNN models are used in this study, and performance evaluation of each model is carried out using different statistical parameters such as mean absolute error (MAE), mean absolute percentage error (MAPE), route mean square error (RMSE), and coefficient of determination (r2-score) for regression problems. From the study, it is concluded that the LSTM RNN model can be utilized for the prediction of the novel corona cases. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.