{"title":"Prediction of the evolution of corona-virus using Machine Learning Technique","authors":"Tokpe Kossi, Subrata Sahana","doi":"10.58260/j.nras.2202.0106","DOIUrl":null,"url":null,"abstract":"The whole world has seen a change in habits in the past two years due to the discovery of the new corona family virus. The new corona virus is classified by The World Health Organization as Covid-19. Everywhere on the planet we are witnessing confirmed decision-making, curfew, restrictions on people, vaccinations, wearing of masks, etc. This paper aims to show how advancement of Machine Learning have provided excellent tools capable of reducing the number of infections while helping medicine in making decisions about testing infected people, reliability, accuracy of tests. We have improved the existing algorithms to produce software that can be able to do the prediction of evolution of corona virus. The implementation is done through Python language. We ensure that the results produced will be reliable and with fewer errors.","PeriodicalId":157556,"journal":{"name":"Global Journal of Novel Research in Applied Sciences (NRAS) [ISSN: 2583-4487]","volume":"65 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-01-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Global Journal of Novel Research in Applied Sciences (NRAS) [ISSN: 2583-4487]","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.58260/j.nras.2202.0106","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
The whole world has seen a change in habits in the past two years due to the discovery of the new corona family virus. The new corona virus is classified by The World Health Organization as Covid-19. Everywhere on the planet we are witnessing confirmed decision-making, curfew, restrictions on people, vaccinations, wearing of masks, etc. This paper aims to show how advancement of Machine Learning have provided excellent tools capable of reducing the number of infections while helping medicine in making decisions about testing infected people, reliability, accuracy of tests. We have improved the existing algorithms to produce software that can be able to do the prediction of evolution of corona virus. The implementation is done through Python language. We ensure that the results produced will be reliable and with fewer errors.