Prediction & Analysis of Covid-19 Cases Using Autoregressive Integrated Moving Average (Arima)

Authors

  • Vedpal J C Bose University of Science & Technology, YMCA, Faridabad, Haryana, India
  • Umesh Kumar J C Bose University of Science & Technology, YMCA, Faridabad, Haryana, India
  • Harish Kumar J C Bose University of Science & Technology, YMCA, Faridabad, Haryana, India
  • Akanshika Gandhi J C Bose University of Science & Technology, YMCA, Faridabad, Haryana, India

Keywords:

Covid-19, ARIMA, time series, prediction

Abstract

For the past three years world is facing the pandemic COVID-19.  For effective handling of COVID-19, accurate decisions should be taken. The accuracy of making any decision is totally dependent on the relevant data and the information. To determine the present situation of the COVID- 19 the collected data from the various states and Union Territories are processed and analyzed. The Collected data from the various resources also helps to forecast the expected confirmed cases in the future. In this paper, the prediction of positive cases of Covid-19 was carried out using the ARIMA time series model. The predictions made in this study were limited to the addition of positive cases of Covid-19 in India. The analysis and visualization of the data were performed using Python. The obtained results of the predictive analysis showed a trend of daily positive cases that tend to rise in the next 98 days from the data used.

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Published

16.07.2023

How to Cite

Vedpal, Kumar, U. ., Kumar, H. ., & Gandhi, A. . (2023). Prediction & Analysis of Covid-19 Cases Using Autoregressive Integrated Moving Average (Arima). International Journal of Intelligent Systems and Applications in Engineering, 11(3), 680–690. Retrieved from https://ijisae.org/index.php/IJISAE/article/view/3274

Issue

Vol. 11 No. 3 (2023)

Section

Research Article

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