About: Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm

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About: Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

Attributes	Values
type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm
Creator	Menon, Vijay
source	ArXiv
abstract	In this paper, we have applied the logistic growth regression model and genetic algorithm to predict the number of coronavirus infected cases that can be expected in upcoming days in India and also estimated the final size and its peak time of the coronavirus epidemic in India.
has issue date	2020-03-26(xsd:dateTime)
has license	arxiv
sha1sum (hex)	ca03944cf1865fc071443afade9dd9b3058fbec9
resource representing a document's title	Prediction of number of cases expected and estimation of the final size of coronavirus epidemic in India using the logistic model and genetic algorithm
resource representing a document's body	covid:ca03944cf1865fc071443afade9dd9b3058fbec9#body_text
is schema:about of	named entity 'estimation' named entity 'cases' named entity 'India' named entity 'genetic algorithm' named entity 'coronavirus epidemic' named entity 'genetic algorithm' named entity 'infected person' named entity 'disease epidemic' named entity 'epidemic' named entity 'severe acute respiratory syndrome coronavirus 2' named entity 'epidemic' named entity 'mathematical models' named entity 'genetic algorithm' named entity 'logistic growth model' named entity 'epidemic' named entity 'epidemic' named entity 'epidemic' named entity 'South Korea' named entity 'mathematical epidemiology' named entity 'empirical relationship' named entity 'logistic model' named entity 'India' named entity 'epidemic' named entity 'randomly assigned' named entity 'coronavirus' named entity 'coronavirus' named entity 'World Health Organization' named entity 'saliva' named entity 'genetic algorithm' named entity 'Genetic algorithm' named entity 'China' named entity 'epidemic' named entity 'logistic model' named entity 'data set' named entity 'expected number' named entity 'India' named entity 'India' named entity 'countries and territories' named entity 'SARS-COV-2' named entity 'discharge from the nose' named entity 'Global optimization' named entity 'pneumonia' named entity 'MATLAB' named entity 'logistic growth' named entity 'epidemic' named entity 'COVID-19 virus' named entity 'Phenomenological model' named entity 'Shanks transformation' named entity 'MATLAB' named entity 'Genetic algorithm' named entity 'Genetic algorithm' named entity 'doubling time' named entity 'infectious disease' named entity 'logistic model' named entity 'COVID' named entity 'logistic model' named entity 'Systems Science and Engineering' named entity 'epidemic' named entity 'infection rate' named entity 'epidemic' named entity 'epidemic' named entity 'coronavirus' named entity 'genetic algorithm' named entity 'nonlinear function' named entity 'logistic model' named entity 'epidemic' named entity 'nonlinear function' named entity 'Johns Hopkins University' named entity 'WHO' named entity 'optimization problem' named entity 'India' named entity 'epidemic' named entity 'India' named entity 'logistic growth' named entity 'ITS' named entity 'regression model' named entity 'logistic model' named entity 'India' named entity 'INDIA' named entity 'PREDICTION' named entity 'peak time' named entity 'NUMBER OF' named entity 'LOGISTIC' named entity 'USING' named entity 'EXPECTED' named entity 'regression model' named entity 'India'

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