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author:

Chen, Xing-lin (Chen, Xing-lin.) [1] | Yu, Long-xing (Yu, Long-xing.) [2] | Lin, Wei-dong (Lin, Wei-dong.) [3] | Yang, Fu-qiang (Yang, Fu-qiang.) [4] | Li, Yi-ping (Li, Yi-ping.) [5] | Tao, Jing (Tao, Jing.) [6] | Cheng, Shuo (Cheng, Shuo.) [7]

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EI

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. © 2023 Elsevier Ltd

Keyword:

Bayesian networks Reliability Urban growth

Community:

  • [ 1 ] [Chen, Xing-lin]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 2 ] [Yu, Long-xing]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 3 ] [Lin, Wei-dong]Fujian Provincial Institute of Architectural Design and Research CO., LTD., Fuzhou; 350001, China
  • [ 4 ] [Yang, Fu-qiang]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350116, China
  • [ 5 ] [Yang, Fu-qiang]Fujian Provincial Key Laboratory of Remote Sensing of Soil Erosion and Disaster Prevention, Fuzhou University, Fuzhou; 350116, China
  • [ 6 ] [Li, Yi-ping]Fujian Provincial Institute of Architectural Design and Research CO., LTD., Fuzhou; 350001, China
  • [ 7 ] [Tao, Jing]School of Law, Fuzhou University, Fuzhou; 350116, China
  • [ 8 ] [Cheng, Shuo]College of Environment and Safety Engineering, Fuzhou University, Fuzhou; 350116, China

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Source :

Reliability Engineering and System Safety

ISSN: 0951-8320

Year: 2023

Volume: 238

9 . 4

JCR@2023

9 . 4 0 0

JCR@2023

ESI HC Threshold:35

JCR Journal Grade:1

CAS Journal Grade:1

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 19

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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