Machine Learning Approach for Forecast Analysis of Novel COVID-19 Scenarios in India DOI Creative Commons
Ankit Kumar Srivastava, Saurabh Tripathi, Sachin Kumar

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 95106 - 95124

Published: Jan. 1, 2022

The novel coronavirus (nCOV) is a new strain that needs to be hindered from spreading by taking effective preventive measures as swiftly possible. Timely forecasting of COVID-19 cases can ultimately support in making significant decisions and planning for implementing measures. In this study, three common machine learning (ML) approaches via linear regression (LR), sequential minimal optimization (SMO) regression, M5P techniques have been discussed implemented disease-2019 (COVID-19) pandemic scenarios. To demonstrate the forecast accuracy aforementioned ML approaches, preliminary sample-study has conducted on first wave scenario different countries including United States America (USA), Italy, Australia. Furthermore, contributions study are extended conducting an in-depth scenarios first, second, third waves India. An accurate model proposed, which constructed basis results models findings research highlight LR potential approach outperforms all other tested herein present scenario. Finally, used likely onset fourth

Language: Английский

Forecasting a New Type of Virus Spread: A Case Study of COVID-19 with Stochastic Parameters DOI Creative Commons
Victor Zakharov, Yu. Е. Balykina, Igor Ilin

et al.

Mathematics, Journal Year: 2022, Volume and Issue: 10(20), P. 3725 - 3725

Published: Oct. 11, 2022

The consideration of infectious diseases from a mathematical point view can reveal possible options for epidemic control and fighting the spread infection. However, predicting modeling new, previously unexplored virus is still difficult. present paper examines possibility using new approach to statistical indicators type based on example COVID-19. important result study description principle dynamic balance epidemiological processes, which has not been used by other researchers modeling. also solving problem future dynamics precisely random values model parameters, defining total number of: cases (C); recovered dead (R); active (I). Intelligent heuristic algorithms are proposed calculating trajectories stochastic called percentage increase in confirmed disease characteristics processes. Examples given application making forecasts considered COVID-19 epidemic, Russia European countries, during first wave epidemic.

Language: Английский

Citations

10
Forecasting SARS-CoV-2 transmission and clinical risk at small spatial scales by the application of machine learning architectures to syndromic surveillance data DOI Open Access
Thomas Ward,

Alexander Johnsen,

Stanley Ng

et al.

Nature Machine Intelligence, Journal Year: 2022, Volume and Issue: 4(10), P. 814 - 827

Published: Oct. 21, 2022

Language: Английский

Citations

10
A new modification CNN using VGG19 and ResNet50V2 for classification of COVID-19 from X-ray radiograph images DOI Open Access
Usman Haruna, Rozniza Ali, Mustafa Man

et al.

Indonesian Journal of Electrical Engineering and Computer Science, Journal Year: 2023, Volume and Issue: 31(1), P. 369 - 369

Published: May 17, 2023

Coronavirus often called COVID-19 is a deadly viral disease that causes as result of severe acute respiratory syndrome coronavirus-2 needs to be identified especially at its early stages, and failure which can lead the further spread virus. Despite with huge success recorded towards use original convolutional neural networks (CNN) deep learning models. However, their architecture modified design versions have more powerful feature layer extractors improve classification performance. This research aimed designing CNN model applied interpret X-rays classify cases improved Therefore, we proposed network (shortened modification CNN) approach uses case by combining VGG19 ResNet50V2 along putting additional dense layers combined extractors. The achieved 99.24%, 98.89%, 98.90%, 99.58%, 99.23% overall accuracy, precision, specificity, sensitivity, F1-Score, respectively. demonstrates results show promising performance in cases.

Language: Английский

Citations

5
A Novel Method for Prediction and Analysis of COVID 19 Transmission Using Machine Learning Based Time Series Models DOI
Suman Mann,

Deepshikha Yadav,

Suresh Muthusamy

et al.

Wireless Personal Communications, Journal Year: 2023, Volume and Issue: 133(3), P. 1935 - 1961

Published: Dec. 1, 2023

Language: Английский

Citations

5
Machine Learning Approach for Forecast Analysis of Novel COVID-19 Scenarios in India DOI Creative Commons
Ankit Kumar Srivastava, Saurabh Tripathi, Sachin Kumar

et al.

IEEE Access, Journal Year: 2022, Volume and Issue: 10, P. 95106 - 95124

Published: Jan. 1, 2022

The novel coronavirus (nCOV) is a new strain that needs to be hindered from spreading by taking effective preventive measures as swiftly possible. Timely forecasting of COVID-19 cases can ultimately support in making significant decisions and planning for implementing measures. In this study, three common machine learning (ML) approaches via linear regression (LR), sequential minimal optimization (SMO) regression, M5P techniques have been discussed implemented disease-2019 (COVID-19) pandemic scenarios. To demonstrate the forecast accuracy aforementioned ML approaches, preliminary sample-study has conducted on first wave scenario different countries including United States America (USA), Italy, Australia. Furthermore, contributions study are extended conducting an in-depth scenarios first, second, third waves India. An accurate model proposed, which constructed basis results models findings research highlight LR potential approach outperforms all other tested herein present scenario. Finally, used likely onset fourth

Language: Английский

Citations

8