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Abstract
Coronavirus has long been considered a global epidemic. It caused the deaths of nearly 7.01 million individuals and caused an economic downturn. The number of verified coronavirus cases is increasing daily, putting the whole human race at danger and putting strain on medical experts to eradicate the disease as rapidly as possible. As a consequence, it is vital to predict the upcoming coronavirus positive patients in order to plan actions in the future. Furthermore, it has been discovered all across the globe that asymptomatic coronavirus patients play a significant part in the disease’s transmission. This prompted us to incorporate similar examples in order to accurately forecast trends. A typical strategy for analysing the rate of pandemic infection is to use time-series forecasting technique. This would assist us in developing better decision support systems. To anticipate COVID-19 active cases for a few countries, we recommended a hybrid model utilizing a fuzzy time series (FTS) model mixed with a non-linear growth model. The coronavirus positive case outbreak has been evaluated for Italy, Brazil, India, Germany, Pakistan, and Myanmar through June 5, 2020 in phase-1, and January 15, 2022 in phase-2, and forecasts active cases for the next 26 and 14 days respectively. The proposed framework fitting effect outperforms individual logistic growth and the fuzzy time series techniques, with R-scores of 0.9992 in phase-1 and 0.9784 in phase-2. The proposed model provided in this article may be utilised to comprehend a country’s epidemic pattern and assist the government in developing better effective interventions.
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1 GITAM School of Technology, GITAM Deemed to Be University, Department of Computer Science & Engineering, Visakhapatnam, India (GRID:grid.449504.8) (ISNI:0000 0004 1766 2457)
2 Woxsen University, School of Technology, Hyderabad, India (GRID:grid.459612.d) (ISNI:0000 0004 1767 065X)
3 GLA University, Department of CEA, Mathura, India (GRID:grid.448881.9) (ISNI:0000 0004 1774 2318)
4 Koneru Lakshmaiah Education Foundation, Department of Computer Science and Engineering, Guntur, India (GRID:grid.449504.8) (ISNI:0000 0004 1766 2457)
5 Khamis Mushait Campus, King Khalid University, Department of Public Health, College of Applied Medical Sciences, Abha, Kingdom of Saudi Arabia (GRID:grid.412144.6) (ISNI:0000 0004 1790 7100)
6 King Khalid University, Civil Engineering Department, College of Engineering, Abha, Saudi Arabia (GRID:grid.412144.6) (ISNI:0000 0004 1790 7100)
7 P. A. College of Engineering (Affiliated to Visvesvaraya Technological University, Belagavi), Department of Mechanical Engineering, Mangaluru, India (GRID:grid.444321.4) (ISNI:0000 0004 0501 2828)
8 Dire-Dawa University, School of Civil Engineering & Architecture, Institute of Technology, Dire Dawa, Ethiopia (GRID:grid.449080.1) (ISNI:0000 0004 0455 6591)