Monitoring Novel Corona Virus using Machine Learning
5th International Conference on Inventive Computation Technologies, ICICT 2022
; : 824-830, 2022.
Article
in English
| Scopus | ID: covidwho-2029243
ABSTRACT
In this article, we are working on a new Pandemic Corona (COVID-19) virus. COVID-19 is an infectious disease that causes serious lung damage. COVID-19 causes a disease in humans and has killed many people around the world. However, the virus has been declared pandemic by the World Health Organization (WHO) and all countries are trying to control and block all locations. In particular, four standard forecasting models have been used linear regression (LR), logistics regression (LOR) and polynomial regression. Many areas of application that require the identification and hierarchy of threats have long used automatic learning models. [1] Machine-based (ML) analysis methods have been shown to be useful in predicting preoperative outcomes and improving decision-making about future actions. Different forecasting methods are widely used to solve forecasting problems. The purpose of this study was to determine the function of COVID-19 research and machine learning applications and algorithms for various purposes [2]. © 2022 IEEE.
COVID-19; Novel corona virus; Polynomial regression; Simple linear regression; Behavioral research; Decision making; Forecasting; Machine learning; Regression analysis; Viruses; Automatic-learning; Forecasting models; Infectious disease; Learning models; Logistics regressions; Machine-learning; World Health Organization
Full text:
Available
Collection:
Databases of international organizations
Database:
Scopus
Language:
English
Journal:
5th International Conference on Inventive Computation Technologies, ICICT 2022
Year:
2022
Document Type:
Article
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