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Urban Resilience of Important Node Cities in Population Migration under the Influence of COVID-19 Based on Mamdani Fuzzy Inference System

Author

Listed:
  • Huilong Wang

    (School of Geography and Planning, Ningxia University, Yinchuan 750021, China)

  • Meimei Wang

    (College of Earth and Environmental Sciences, Lanzhou University, Lanzhou 730000, China)

  • Rong Yang

    (School of Geography and Planning, Ningxia University, Yinchuan 750021, China)

  • Huijuan Yang

    (School of Geography and Planning, Ningxia University, Yinchuan 750021, China)

Abstract

COVID-19 has resulted in a great inconvenience and has had a severe impact on the economy and residents’ daily life in China and even the world. Urban resilience, as the key representation of social and economic stability, can directly reflect the development and stability of cities. In addition, the Mamdani fuzzy inference system (MFIS), as one of the commonly used fuzzy inference systems, has been successfully applied in various application problems involving imprecise or vague information since it was proposed. In this paper, we mainly consider the urban resilience of 50 important node cities for population migration (50INCPM) in China in 2020 under the influence of COVID-19. We apply MFIS for approximating the urban resilience index (URI) based on multiple inputs, which includes the population density resilience index (PRI), gross domestic product per capita resilience index (GRI), in-degree centrality resilience index (IRI), out-degree centrality resilience index (ORI), confirmed cases number (CCN), recovery rate (RR) and mortality rate (MR). Meanwhile, based on the big data of population migration and COVID-19 data in China from 15 January to 15 March in 2020, we calculate the URI of 50INCPM in China in 2020 under the influence of COVID-19. Moreover, we show the spatial difference of URI and its changes in different stages. The results show that (1) the URI of 50INCPM decreases from the eastern coastal area to the western inland, and the cities with URI more than 0.5 are gathered in the eastern coastal area of China. As COVID-19 is controlled, the URI is gradually rising, and the growth rate of URI in southeast coastal cities exceeds that of inland cities. (2) The second-tier and third-tier cities have stronger resilience in the case of large-scale emergencies. (3) There exists a positive correlation in URI and RR. The expectation of the research finding gives a basis for judging the economic and social situation under the impact of COVID-19, which can help local governments accurately judge city resilience, and provide a reference for the decision on resuming production and work, so it is of positive significance for national economic resilience and social stability. Finally, on the basis of universal vaccine coverage, we hold that the GOC should promote the cities’ resilience in China, especially in the first-tier city in inland China (Beijing, Shanghai, Guangzhou and Shenzhen). On the other hand, on the premise of implementing epidemic prevention and control measures, local governments should stimulate the resilience of each city in terms of population and economy.

Suggested Citation

  • Huilong Wang & Meimei Wang & Rong Yang & Huijuan Yang, 2023. "Urban Resilience of Important Node Cities in Population Migration under the Influence of COVID-19 Based on Mamdani Fuzzy Inference System," Sustainability, MDPI, vol. 15(19), pages 1-22, September.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:19:p:14401-:d:1251755
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    References listed on IDEAS

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