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Deep Neural Network-Based Prediction of the COVID-19 Spread in India

Rishika Chauhan, Shefali Sharma, Rahul Pachauri

Abstract


In this study, a DNN model based on LM algorithm is utilized for forecasting the number of daily new infected, deceased, and recovered cases of COVID-19 in India. Different statistical parameters were used to test the efficacy of the developed model. Daily details of total cases from 1st March to 31st December 2020 were used to predict new confirmed, deceased, and recovered cases for next 80 days. The proposed DNN model provides good agreement with the actual data. As COVID-19 is a contagious disease so continuous evaluation of the existing strategy is highly essential to fight with it.

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References


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