Selected article for: "active number and machine learning"
Author: Wadhwa, Parth; Aishwarya; Tripathi, Amrendra; Singh, Prabhishek; Diwakar, Manoj; Kumar, Neeraj
Title: Predicting the Time Period of Extension of Lockdown due to Increase in Rate of COVID-19 Cases in India using Machine Learning
  • Cord-id: 1cjwobtc
  • Document date: 2020_8_28
    • ID: 1cjwobtc
    Snippet: The research paper proposes a methodology to predict the extension of lockdown in order to eradicate COVID-19 from India. All the concepts related to Coronavirus, its history, prevention and cure is explained in the research paper. Concept used to predict the number of active cases, deaths and recovery is Linear Regression which is an application of machine learning. Extension of lockdown is predicted on the basis of predicted number of active cases, deaths and recovery all over India. To predic
    Document: The research paper proposes a methodology to predict the extension of lockdown in order to eradicate COVID-19 from India. All the concepts related to Coronavirus, its history, prevention and cure is explained in the research paper. Concept used to predict the number of active cases, deaths and recovery is Linear Regression which is an application of machine learning. Extension of lockdown is predicted on the basis of predicted number of active cases, deaths and recovery all over India. To predict the number of active cases, deaths and recovery, date wise analysis of current data was done and necessary parameters like daily recovery, daily deaths, increase rate of covid-19 cases were included. Graphical representation of each analysis and prediction was done in order to make predicted results more understandable. The combined analysis was performed at the end which included the final result of total cases of coronavirus in India. Combined analysis included the no. of cases from start of COVID-19 to the predicted end of cases all over India. [copyright information to be updated in production process]

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