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Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries

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  • Mahmoudi, Mohammad Reza
  • Baleanu, Dumitru
  • Mansor, Zulkefli
  • Tuan, Bui Anh
  • Pho, Kim-Hung

Abstract

The numbers of confirmed cases of new coronavirus (Covid-19) are increased daily in different countries. To determine the policies and plans, the study of the relations between the distributions of the spread of this virus in other countries is critical. In this work, the distributions of the spread of Covid-19 in Unites States America, Spain, Italy, Germany, United Kingdom, France, and Iran were compared and clustered using fuzzy clustering technique. At first, the time series of Covid-19 datasets in selected countries were considered. Then, the relation between spread of Covid-19 and population's size was studied using Pearson correlation. The effect of the population's size was eliminated by rescaling the Covid-19 datasets based on the population's size of USA. Finally, the rescaled Covid-19 datasets of the countries were clustered using fuzzy clustering. The results of Pearson correlation indicated that there were positive and significant between total confirmed cases, total dead cases and population's size of the countries. The clustering results indicated that the distribution of spreading in Spain and Italy was approximately similar and differed from other countries.

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  • Mahmoudi, Mohammad Reza & Baleanu, Dumitru & Mansor, Zulkefli & Tuan, Bui Anh & Pho, Kim-Hung, 2020. "Fuzzy clustering method to compare the spread rate of Covid-19 in the high risks countries," Chaos, Solitons & Fractals, Elsevier, vol. 140(C).
  • Handle: RePEc:eee:chsofr:v:140:y:2020:i:c:s0960077920306263
    DOI: 10.1016/j.chaos.2020.110230
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    References listed on IDEAS

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    1. A. R. Nematollahi & A. R. Soltani & M. R. Mahmoudi, 2017. "Periodically correlated modeling by means of the periodograms asymptotic distributions," Statistical Papers, Springer, vol. 58(4), pages 1267-1278, December.
    2. Mohammad Reza Mahmoudi & Mohsen Maleki & Abbas Pak, 2018. "Testing the equality of two independent regression models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 47(12), pages 2919-2926, June.
    3. Mohammad Reza Mahmoudi & Mohammad Hossein Heydari & Zakieh Avazzadeh, 2019. "Testing the difference between spectral densities of two independent periodically correlated (cyclostationary) time series models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(9), pages 2320-2328, May.
    4. Heydari, M.H. & Avazzadeh, Z. & Mahmoudi, M.R., 2019. "Chebyshev cardinal wavelets for nonlinear stochastic differential equations driven with variable-order fractional Brownian motion," Chaos, Solitons & Fractals, Elsevier, vol. 124(C), pages 105-124.
    5. Mohammad Reza Mahmoudi & Mohsen Maleki, 2017. "A new method to detect periodically correlated structure," Computational Statistics, Springer, vol. 32(4), pages 1569-1581, December.
    6. Fanelli, Duccio & Piazza, Francesco, 2020. "Analysis and forecast of COVID-19 spreading in China, Italy and France," Chaos, Solitons & Fractals, Elsevier, vol. 134(C).
    7. Mohammad Reza Mahmoudi & Roya Nasirzadeh & Mahmoud Mohammadi, 2019. "On the ratio of two independent skewnesses," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 48(7), pages 1721-1727, April.
    8. Abdol Rassoul Zarei & Mohammad Reza Mahmoudi, 2017. "Evaluation of changes in RDIst index effected by different Potential Evapotranspiration calculation methods," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(15), pages 4981-4999, December.
    9. Mahmoudi, Mohammad Reza & Heydari, Mohammad Hossein & Roohi, Reza, 2019. "A new method to compare the spectral densities of two independent periodically correlated time series," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 160(C), pages 103-110.
    10. Mohammad Reza Mahmoudi & Marziyeh Mahmoudi & Elaheh Nahavandi, 2016. "Testing the difference between two independent regression models," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 45(21), pages 6284-6289, November.
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