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Topological Data Analysis of COVID-19 Using Artificial Intelligence and Machine Learning Techniques in Big Datasets of Hausdorff Spaces

dc.contributor.authorOnyango, Allan
dc.contributor.authorOkelo, Benard
dc.contributor.authorOmollo, Richard
dc.date.accessioned2023-08-01T09:10:44Z
dc.date.available2023-08-01T09:10:44Z
dc.date.issued2023-03-24
dc.identifier.urihttp://ir.jooust.ac.ke:8080/xmlui/handle/123456789/12725
dc.description.abstractIn this paper, we carry out an in-depth topological data analysis of COVID-19 pandemic using artificial intelligence and machine learning techniques. We show the distribution patterns of the pandemic all over the world, when it was at its peak, with respect to big datasets in Hausdorff spaces. The results show that the world areas, which experience a lot of cold seasons, were affected most.en_US
dc.language.isoenen_US
dc.publisherJournal of Data Science and Intelligent Systemsen_US
dc.subjectArtificial Intelligenceen_US
dc.subjectMachine Learningen_US
dc.subjectTopological Data Analysisen_US
dc.subjectCOVID-19en_US
dc.titleTopological Data Analysis of COVID-19 Using Artificial Intelligence and Machine Learning Techniques in Big Datasets of Hausdorff Spacesen_US
dc.typeArticleen_US


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