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COVID-19 Outbreak Prediction using Artificial Neural Network: A Review

by Manu Tyagi, Peeyush Kumar, Mayank Agarwal, Unnati Gangwar, Jayati Bhardwaj, Priyanshu Murari
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 184 - Number 2
Year of Publication: 2022
Authors: Manu Tyagi, Peeyush Kumar, Mayank Agarwal, Unnati Gangwar, Jayati Bhardwaj, Priyanshu Murari
10.5120/ijca2022921979

Manu Tyagi, Peeyush Kumar, Mayank Agarwal, Unnati Gangwar, Jayati Bhardwaj, Priyanshu Murari . COVID-19 Outbreak Prediction using Artificial Neural Network: A Review. International Journal of Computer Applications. 184, 2 ( Mar 2022), 48-51. DOI=10.5120/ijca2022921979

@article{ 10.5120/ijca2022921979,
author = { Manu Tyagi, Peeyush Kumar, Mayank Agarwal, Unnati Gangwar, Jayati Bhardwaj, Priyanshu Murari },
title = { COVID-19 Outbreak Prediction using Artificial Neural Network: A Review },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2022 },
volume = { 184 },
number = { 2 },
month = { Mar },
year = { 2022 },
issn = { 0975-8887 },
pages = { 48-51 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume184/number2/32308-2022921979/ },
doi = { 10.5120/ijca2022921979 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T01:20:28.126496+05:30
%A Manu Tyagi
%A Peeyush Kumar
%A Mayank Agarwal
%A Unnati Gangwar
%A Jayati Bhardwaj
%A Priyanshu Murari
%T COVID-19 Outbreak Prediction using Artificial Neural Network: A Review
%J International Journal of Computer Applications
%@ 0975-8887
%V 184
%N 2
%P 48-51
%D 2022
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The global spread of the COVID-19 outbreak has led to studies on a variety of topics, including predictions of predictable cases. Because it helps to identify the need to deal with epidemic situations. We used artificial neural networks (ANNs) in this study to predict the number of COVID-19 cases in Brazil, Mexico, India, and Italy in the coming days. The Prey Predator Method (PPA) is a type of meta-heuristic algorithm for training guessing models. The root function of the mean squared error (RMSE) and the correlation coefficient were used to evaluate the performance of the target ANN models (R). ANN models performed much better than other models in Brazil, Mexico, India, and Italy in terms of disease rates (active cases), recovery, and death. The simulation results for the ANN models predict the values accurately. Traditional monolithic neural networks have a much higher percentage of predictor errors than meta-heuristic algorithms. The report shows an estimated daily morbidity, recovery and mortality in Brazil, Mexico, India and Italy in early 2021.

References
  1. ZU, Z.Y., Jiang, M.D., XU, P.P., Chen, W., Ni, Q.Q., Lu, G.M., and Zhang, L.J. ZU, Z.Y., Jiang, M.D., XU, P.P., Chen, W., Ni, Q.Q., Lu, G.M., and Zhang, L.J. Chinese view on Corona virus Disease 2019 (COVID-19). 200490, Radiology 2020.
  2. Tartaglione, E.; Barbano, C.A.; Berzovini, C.; Calandri, M.; Grangetto, M. Reveals COVID-19 from chest X-ray for in-depth reading: Obstacle racing with little data. Int. J. Nature. Res. Public Health 2020, 17, 6933.
  3. Kong, W.; Agarwal, P.P. Appearance image of chest infection with COVID-19. Radiol. Cardiothorac. Illustration 2020, 2, e200028.
  4. Zhou, P.; Yang, X.-L.; Wang, X.-G.; Hu, B.; Zhang, L.; Zhang, W.; Si, H.-R.; Zhu, Y.; Li, B.; Huang, C.-L.; et al An outbreak of pneumonia associated with a new corona virus may be the origin of bats. Nature 2020, 579, 270–273.
  5. Li, X.; Geng, M.; Peng, Y.; Meng, L.; Lu, S. Molecular immune pathogenesis and diagnosis of COVID-19. J. Pharm. Anal. 2020, 10, 102–108.
  6. Wang, L.; Lin, Z.Q.; Wong, A. Covid-net: Design of a deep neural network designed to detect COVID-19 cases in chest x-ray images. Science Rep. 2020, 10, 19549.
  7. Chen, Y.; Cheng, J.; Jiang, Y.; Liu, K. A flexible time-delayed system with an external source for the 2019-nCoV outbreak. Application. Indunu. 2020, 1–12.
  8. Fu, L .; Wang, B .; Yuan, T .; Chen, X .; AO, Y .; Fitzpatrick,T .; Li, P .; Zhou, Y .; Duan, Q .; et al. Clinical features of corona virus 2019 (COVID-19) in China: A systematic review and meta-analysis. J. Pour. 2020, 80, 656-665.
  9. Cascella, M.; Rajnik, M.; Cuomo, A.; Dulebohn, S.C.; Di Napoli, R. Features, Diagnosis and Treatment of Corona virus (COVID-19). Statpearls; StatPearls Publishing: Treasure Island, FL, USA, 2020.
  10. Cohen, J.P.; Morrison, P.; Dao, L.; Roth, K.; Duong, T.Q.; Ghassemi, M. COVID-19 image data collection: Predictable predictions are future. arXiv 2019, arXiv:200611988.
  11. Gao, Z.; Xu, Y.; Sun, C.; Wang, X.; Guo, Y.; Qiu, S.; Ma, K.. Systematic review of asymptomatic infection with COVID-19.J. Microbiol. Immunol. Pour 2020.
  12. Khaleque, A.; Sen, P. A powerful analysis of the Ebola outbreak in West Africa. Science. Rep. 2017, 7, 42594.
  13. Zakary, O.; Larrache, A.; Rachik, M.; Elmouki, Outcome of awareness programs and prevention activities in controlling the spread of HIV/AIDS: A multidisciplinary SIR model. Adv. Differ. Equ. 2016, 2016, 169.
  14. Godio, A.; Pace, F.; Vergnano, A. SEIR SARS Italian Epidemic Model- CoV-2 Using Computer Intelligence. Int. J. Nature. Res. Public Health 2020, 17, 3535.
  15. Berger, D.W.; Herkenhoff, K.F.; Mongey, S. An infectious disease model with diagnostic and conditional classification. Natl. Bur. Econ.
Index Terms

Computer Science
Information Sciences

Keywords

COVID 19 ANN SIR SEIR PSO MLPNN Prey predator algorithm (PPA)

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