Survey on Forecasting the vulnerability of Covid 19 in Tamil Nadu

Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linear regression (LR) a Machine Learning model is used to forecast the number of patien...

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Bibliographic Details
Published inJournal of physics. Conference series Vol. 1767; no. 1; pp. 12006 - 12017
Main Authors Ananthi, P., Jabeen Begum, S., Latha Jothi, V., Kayalvili, S., Gokulraj, S.
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.02.2021
Subjects
Decision analysis
Decision making
Forecasting
Infections
Machine learning
Mathematical models
Pandemics
Physics
Prediction models
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Summary:Predictive and analytic models for forecasting the vulnerability and recovery rate of patients who are affected by COVID 19 are made in this project for good analysis and better decision-making. In this project, linear regression (LR) a Machine Learning model is used to forecast the number of patients will get the infection in near future. By simulating SIRD model, the infection spread and recovery rate of the disease in a geographic region can be predicted. The vulnerability of the disease is checked by observing the transmission of disease over a period. In addition to this many info graphic models and graphs are created for easy understanding of data to get more insights about the disease. However, these prediction models enable us to make quick response of pandemic and to bring a conclusion to the disease. INDEX TERMS: Covid 19, data science, machine learning, prediction, analysis, pandemic, recovery and infection.
ISSN:1742-6588
1742-6596
DOI:10.1088/1742-6596/1767/1/012006