Vol. 1 No. 1 (2023): Jan/June - Issue - 01
Articles

A Comparative Analysis of ARIMA Model and LSTM Network in Predicting COVID-19 Outcomes in India

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  • Premavathi T
Premavathi T
Department of Computer Engineering, Marwadi University, Rajkot, India
DOI: https://doi.org/10.5281/zenodo.8267919

Published 2023-08-21

Keywords

  • Covid-19,
  • time series forecasting,
  • ARIMA model,
  • auto regression,
  • linear regression,
  • random forest,
  • SVM
    • ...More
    Less

How to Cite

Premavathi T. (2023). A Comparative Analysis of ARIMA Model and LSTM Network in Predicting COVID-19 Outcomes in India. Milestone Transactions on Medical Technometrics, 1(1), 25–36. https://doi.org/10.5281/zenodo.8267919

Abstract

The COVID-19 pandemic is a profound concern and an urgent issue that needs to be addressed first and foremost globally. It strongly affects all areas of life from public health, health, education, economy as well as human freedom of movement. The worrying thing is that there is no specific treatment as well as prevention in the early stages. This infectious disease could not be stopped anytime soon. With the rapid spread of the disease, the global health system collapsed because it did not anticipate the danger with its exponential rate of spread. The application of methods to predict the number of infections in machine learning can contribute to limiting the vulnerability to humanity. By predicting the number of cases, we can be better prepared, such as providing more hospital beds, producing more medical equipment, allocating more medical staff to areas with a sharp increase in the number of infections. This solution helps the government to have the necessary references to make the best and fastest decisions. This paper applies two models in machine learning that are Autoregressive-Integrated-Moving-Average (ARIMA) and Long Short Term Memory (LSTM) to choose the best solution to the problem
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