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Urban resilience assessment from the multidimensional perspective using dynamic Bayesian network: A case study of Fujian Province, China

Author

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  • Chen, Xing-lin
  • Yu, Long-xing
  • Lin, Wei-dong
  • Yang, Fu-qiang
  • Li, Yi-ping
  • Tao, Jing
  • Cheng, Shuo

Abstract

Pursuing the high-quality urbanisation and improving urban system reliability are the current goal of urban development. Urban resilience reflects the reliability of a city in coping with external and internal disturbances. Therefore, the urban system reliability can be quantified by assessing urban resilience. Simultaneously, urban resilience assessments can identify vulnerabilities that affect the urban system reliability. Based on this, targeted decisions are proposed to enhance the reliability, stability and safety of urban systems. This study constructs an assessment indicator system to quantitatively estimate the reliability of urban systems and develops a dynamic urban resilience assessment model by combining it with a dynamic network framework that accounts for time-varying factors. The model estimates the urban system reliability from a resilience perspective and identifies vulnerabilities in urban resilience. The applicability of the model is verified using Fujian Province as a research case. The case study uses annual urban data from 2016 to 2021, which is outstanding in terms of data objectivity. The results provide important insights for practitioners and researchers in optimising urban resilience, improving urban system reliability and formulating urban development strategies.

Suggested Citation

  • Chen, Xing-lin & Yu, Long-xing & Lin, Wei-dong & Yang, Fu-qiang & Li, Yi-ping & Tao, Jing & Cheng, Shuo, 2023. "Urban resilience assessment from the multidimensional perspective using dynamic Bayesian network: A case study of Fujian Province, China," Reliability Engineering and System Safety, Elsevier, vol. 238(C).
    • Handle: RePEc:eee:reensy:v:238:y:2023:i:c:s0951832023003836
    DOI: 10.1016/j.ress.2023.109469
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    Cited by:

    1. Chen, Xing-lin & Huang, Zong-hou & Ge, Fan-liang & Lin, Wei-dong & Yang, Fu-qiang, 2024. "A probabilistic analysis method for evaluating the safety & resilience of urban gas pipeline network," Reliability Engineering and System Safety, Elsevier, vol. 248(C).
    2. Yu, Yaocheng & Shuai, Bin & Huang, Wencheng, 2024. "Resilience evaluation of train control on-board system based on multi-dimensional continuous-time Bayesian network," Reliability Engineering and System Safety, Elsevier, vol. 246(C).

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