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https://gnanaganga.inflibnet.ac.in:8443/jspui/handle/123456789/1084
Title: | Analyzing Data on the Spread of COVID-19 using Statistical Tools to Predict the Inflexion Point of the Virus in Italy |
Authors: | Nirbhay Narang, Mehul Jangir |
Keywords: | Coronavirus, Logistic functions Curve-fitting Inflection points Infection prediction Python |
Issue Date: | 2020 |
Publisher: | Indian Journal of Computer Science |
Abstract: | The outbreak of the novel coronavirus COVID-19 had resulted in deaths of over 24,000 people by April 20, 2020. The goal of this paper is to use and apply principles of statistics and machine learning on COVID-19 datasets available online to predict the inflection point of the spread of the virus. The inflection point, for the purpose of this paper, is defined as a point in time in days after the outbreak of the virus at which there is a change in the direction of the rate of spreading of the virus. We are using available libraries to fit the data a logistic function. |
URI: | http://gnanaganga.inflibnet.ac.in:8080/jspui/handle/123456789/1084 |
Appears in Collections: | Article Archives |
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File | Description | Size | Format | |
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Analyzing Data on the Spread of COVID-19 Using Statistical.pdf Restricted Access | Analyzing Data on the Spread of COVID-19 Using | 1.14 MB | Adobe PDF | View/Open Request a copy |
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