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Application of Neutrosophic Similarity Measures in Covid-19

Author

Listed:
  • Rakhal Das

    (Tripura University Agartala)

  • Anjan Mukherjee

    (Tripura University Agartala)

  • Binod Chandra Tripathy

    (Tripura University Agartala)

Abstract

The contemporary situation of the world is very pathetic due to the spread of COVID-19. In this article, we have prepared a decision making model on COVID-19 pandemic patients with the help of the neutrosophic similarity measures. The model is to predict the COVID-19 patents for testing positive and testing negative. The decision making is based on the testing result of the COVID-19 cases. We have used the neutrosophic similarity measure theory and the distance function. We have used the C-programming for finding the result of the suspected patients.

Suggested Citation

  • Rakhal Das & Anjan Mukherjee & Binod Chandra Tripathy, 2022. "Application of Neutrosophic Similarity Measures in Covid-19," Annals of Data Science, Springer, vol. 9(1), pages 55-70, February.
    • Handle: RePEc:spr:aodasc:v:9:y:2022:i:1:d:10.1007_s40745-021-00363-8
    DOI: 10.1007/s40745-021-00363-8
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    References listed on IDEAS

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    1. Pinaki Majumdar & S. K. Samanta, 2008. "Similarity Measure Of Soft Sets," New Mathematics and Natural Computation (NMNC), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 1-12.
    2. Sanjay Kumar, 2020. "Monitoring Novel Corona Virus (COVID-19) Infections in India by Cluster Analysis," Annals of Data Science, Springer, vol. 7(3), pages 417-425, September.
    3. James M. Tien, 2017. "Internet of Things, Real-Time Decision Making, and Artificial Intelligence," Annals of Data Science, Springer, vol. 4(2), pages 149-178, June.
    4. Aboma Temesgen & Abdisa Gurmesa & Yehenew Getchew, 2018. "Joint Modeling of Longitudinal CD4 Count and Time-to-Death of HIV/TB Co-infected Patients: A Case of Jimma University Specialized Hospital," Annals of Data Science, Springer, vol. 5(4), pages 659-678, December.
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