The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Digital Archiving Policy
  • Promote your Publication
  • Metadata Harvesting (OAI2)

IJACSA

  • About the Journal
  • Call for Papers
  • Editorial Board
  • Author Guidelines
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Fees/ APC
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors
  • SUSAI-EE 2025
  • ICONS-BA 2025
  • IoT-BLOCK 2025

Future of Information and Communication Conference (FICC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Computing Conference

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC)

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Editorial Board
  • Guidelines
  • Submit
  • Current Issue
  • Archives
  • Indexing
  • Fees
  • Reviewers
  • Subscribe

DOI: 10.14569/IJACSA.2022.0130521
PDF

Analysis and Prediction of COVID-19 by using Recurrent LSTM Neural Network Model in Machine Learning

Author 1: N. P. Dharani
Author 2: Polaiah Bojja

International Journal of Advanced Computer Science and Applications(IJACSA), Volume 13 Issue 5, 2022.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: As we all know that corona virus is announced as pandemic in the world by WHO. It is spreaded all over the world with few days of time. To control this spreading, every citizen maintains social distance and self preventive measures are the best strategies. As of now many researchers and scientists are continuing their research in finding out the exact vaccine. The machine learning model finds that the corona virus disease behaves in exponential manner. To abolish the consequence of this pandemic, an efficient step should be taken to analyze this disease. In this paper, a recurrent neural network model is chosen to predict the number of active cases in a particular state. To do this prediction of active cases, we need database. The database of COVID-19 is downloaded from KAGGLE website and is analyzed by applying recurrent LSTM neural network with univariant features to predict for the number of active cases of patients suffering from corona virus. The downloaded database is divided into training and testing the chosen neural network model. The model is trained with the training data set and tested with testing dataset to predict the number of active cases in a particular state here we have concentrated on Andhra Pradesh state.

Keywords: COVID-19; corona virus; KAGGLE; LSTM neural network; machine learning

N. P. Dharani and Polaiah Bojja, “Analysis and Prediction of COVID-19 by using Recurrent LSTM Neural Network Model in Machine Learning” International Journal of Advanced Computer Science and Applications(IJACSA), 13(5), 2022. http://dx.doi.org/10.14569/IJACSA.2022.0130521

@article{Dharani2022,
title = {Analysis and Prediction of COVID-19 by using Recurrent LSTM Neural Network Model in Machine Learning},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2022.0130521},
url = {http://dx.doi.org/10.14569/IJACSA.2022.0130521},
year = {2022},
publisher = {The Science and Information Organization},
volume = {13},
number = {5},
author = {N. P. Dharani and Polaiah Bojja}
}



Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

IJACSA

Upcoming Conferences

IntelliSys 2025

28-29 August 2025

  • Amsterdam, The Netherlands

Future Technologies Conference 2025

6-7 November 2025

  • Munich, Germany

Healthcare Conference 2026

21-22 May 2026

  • Amsterdam, The Netherlands

Computing Conference 2026

9-10 July 2026

  • London, United Kingdom

IntelliSys 2026

3-4 September 2026

  • Amsterdam, The Netherlands

Computer Vision Conference 2026

15-16 October 2026

  • Berlin, Germany
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© The Science and Information (SAI) Organization Limited. All rights reserved. Registered in England and Wales. Company Number 8933205. thesai.org