Advanced Deep Learning Model for Future Forecasting of COVID-19. Issue 1 (May 2021)

• Record Type: Journal Article
• Authors: Lavanya, ; Suganya, R; Kanmani, R.; Godwin Joyal, S.
• Is Part Of: Journal of physics. Volume 1916:Issue 1(2021)
• Publication Date: 2021-05
• Subjects: Corona virus -- COVID-19 -- SVM -- LSTIA -- Machine Learning -- LASSO; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1916/1/012147
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: The roll out of corona virus (COVID-19) in the entire every country has put the mankind in danger. The assets of the absolute biggest economies are worried because of the enormous infectivity and contagiousness of this sickness. The capacity of machine learning models to conjecture the quantity and number of impending peoples influenced by corona virus which is by and by took as a possible danger for humankind. Specifically, Three layer of determining models, least outright shrinkage and choice administrator (LASSO) Support vector Machine – deep learning have been utilized in this investigation to estimate the undermining components of corona virus. Minimum Three kinds of expectations are proposed by every one of the systems, like the quantity of recently tainted reports, the quantity of passing's, and the quantity of recuperations But in the can't foresee the exact outcome for the patients. To defeat the issue, Proposed strategy utilizing the long Short-term Integrated Average (LSTIA) foresee the quantity of COVID-19 cases in next 30 days ahead and impact of preventive estimates like social segregation and lockdown on the Roll out of corona virus.