COVID-19 Epidemic Process Simulation Using ARIMA Model
International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering -Synergetic Engineering, ICTM 2021
; 367 LNNS:353-363, 2022.
Article
in English
| Scopus | ID: covidwho-1750535
ABSTRACT
The substantial ascendant trend within the number of daily infected new cases with coronavirus around the world is a warning, and several other researchers are utilizing various mathematical and machine learning-based prediction models to forecast the long-term trend of the COVID-19 pandemic. During this research, the Autoregressive Integrated Moving Average or ARIMA model was implemented to forecast the COVID-19 expected daily number of cases in Ukraine. We implemented Autoregressive Integrated Moving Average for this research. The forecasting results showed that the trend in Ukraine will continue ascending and should reach up to more than 1.8 million total cases if stringent precautionary and control measures don’t get implemented to prohibit the spread of COVID-19. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
Full text:
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Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
International Scientific and Technical Conference on Integrated Computer Technologies in Mechanical Engineering -Synergetic Engineering, ICTM 2021
Year:
2022
Document Type:
Article
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