Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique
Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs...
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GJESM Publisher
2020-08-01
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| Series: | Global Journal of Environmental Science and Management |
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| Online Access: | https://www.gjesm.net/article_39823_ea9f7281c4739ee2ded77ec2f0764632.pdf |
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| author | S.K. Tamang P.D. Singh B. Datta |
| author_facet | S.K. Tamang P.D. Singh B. Datta |
| author_sort | S.K. Tamang |
| collection | DOAJ |
| description | Artificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Covid-19 number of rising cases and death cases in India, USA, France, and UK, considering the progressive trends of China and South Korea. In this paper, three cases are considered to analyze the outbreak of Covid-19 pandemic viz., (i) forecasting as per the present trend of rising cases of different countries (ii) forecasting of one week following up with the improvement trends as per China and South Korea, and (iii) forecasting if followed up the progressive trends as per China and South Korea before a week. The results have shown that ANN can efficiently forecast the future cases of COVID 19 outbreak of any country. The study shows that the confirmed cases of India, USA, France and UK could be about 50,000 to 1,60,000, 12,00,000 to 17,00,000, 1,40,000 to 1,50,000 and 2,40,000 to 2,50,000 respectively and may take about 2 to 10 months based on progressive trends of China and South Korea. Similarly, the death toll for these countries just before controlling could be about 1600 to 4000 for India, 1,35,000 to 1,00,000 for USA, 40,000 to 55,000 for France, 35,000 to 47,000 for UK during the same period of study. |
| format | Article |
| id | doaj-art-74dd31c926a542c080c109f8f4bf861c |
| institution | Kabale University |
| issn | 2383-3572 2383-3866 |
| language | English |
| publishDate | 2020-08-01 |
| publisher | GJESM Publisher |
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| series | Global Journal of Environmental Science and Management |
| spelling | doaj-art-74dd31c926a542c080c109f8f4bf861c2025-02-02T16:44:47ZengGJESM PublisherGlobal Journal of Environmental Science and Management2383-35722383-38662020-08-016Special Issue (Covid-19)536410.22034/GJESM.2019.06.SI.0639823Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting techniqueS.K. Tamang0P.D. Singh1B. Datta2Department of Mechanical Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, IndiaDepartment of Electrical Engineering, North Eastern Regional Institute of Science and Technology, Itanagar, IndiaDepartment of Electrical Engineering, National Institute of Technology, Yupia, IndiaArtificial neural network is considered one of the most efficient methods in processing huge data sets that can be analyzed computationally to reveal patterns, trends, prediction, forecasting etc. It has a great prospective in engineering as well as in medical applications. The present work employs artificial neural network-based curve fitting techniques in prediction and forecasting of the Covid-19 number of rising cases and death cases in India, USA, France, and UK, considering the progressive trends of China and South Korea. In this paper, three cases are considered to analyze the outbreak of Covid-19 pandemic viz., (i) forecasting as per the present trend of rising cases of different countries (ii) forecasting of one week following up with the improvement trends as per China and South Korea, and (iii) forecasting if followed up the progressive trends as per China and South Korea before a week. The results have shown that ANN can efficiently forecast the future cases of COVID 19 outbreak of any country. The study shows that the confirmed cases of India, USA, France and UK could be about 50,000 to 1,60,000, 12,00,000 to 17,00,000, 1,40,000 to 1,50,000 and 2,40,000 to 2,50,000 respectively and may take about 2 to 10 months based on progressive trends of China and South Korea. Similarly, the death toll for these countries just before controlling could be about 1600 to 4000 for India, 1,35,000 to 1,00,000 for USA, 40,000 to 55,000 for France, 35,000 to 47,000 for UK during the same period of study.https://www.gjesm.net/article_39823_ea9f7281c4739ee2ded77ec2f0764632.pdfann-curve fittingartificial neural network (ann)coronavirus (covid-19)forecast modelling |
| spellingShingle | S.K. Tamang P.D. Singh B. Datta Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique Global Journal of Environmental Science and Management ann-curve fitting artificial neural network (ann) coronavirus (covid-19) forecast modelling |
| title | Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique |
| title_full | Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique |
| title_fullStr | Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique |
| title_full_unstemmed | Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique |
| title_short | Forecasting of Covid-19 cases based on prediction using artificial neural network curve fitting technique |
| title_sort | forecasting of covid 19 cases based on prediction using artificial neural network curve fitting technique |
| topic | ann-curve fitting artificial neural network (ann) coronavirus (covid-19) forecast modelling |
| url | https://www.gjesm.net/article_39823_ea9f7281c4739ee2ded77ec2f0764632.pdf |
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