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

Authors

  • Allan Onyango Department of Pure and Applied Mathematics, Jaramogi Oginga Odinga University of Science and Technology, Kenya https://orcid.org/0009-0000-5104-0887
  • Benard Okelo Department of Pure and Applied Mathematics, Jaramogi Oginga Odinga University of Science and Technology, Kenya https://orcid.org/0000-0003-3963-1910
  • Richard Omollo Department of Computer Science and Software Engineering, Jaramogi Oginga Odinga University of Science and Technology, Kenya

DOI:

https://doi.org/10.47852/bonviewJDSIS3202701

Keywords:

artificial intelligence, machine learning, topological data analysis, COVID-19, python

Abstract

In this paper, we carry out an in-depth topological data analysis (TDA) of COVID-19 pandemic using artificial intelligence (AI) and Machine Learning (ML) techniques. We show the distribution patterns of pandemic all over the world when it was at its peak with respect to big data sets in Hausdorff spaces. The results show that the world areas which experience a lot of cold seasons were affected most.

 

Received: 31 January 2023 | Revised: 6 March 2023 | Accepted: 21 March 2023

 

Conflicts of Interest

The authors declare that they have no conflicts of interest to this work.


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Published

2023-03-24

How to Cite

Onyango, A., Okelo, B., & Omollo, R. (2023). Topological Data Analysis of COVID-19 Using Artificial Intelligence and Machine Learning Techniques in Big Datasets of Hausdorff Spaces. Journal of Data Science and Intelligent Systems, 1(1), 55–64. https://doi.org/10.47852/bonviewJDSIS3202701

Issue

Section

Research Articles