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基于云模型和逼近理想解排序法的城市雨水抗灾能力评估方法。

Urban Stormwater Resilience Assessment Method Based on Cloud Model and TOPSIS.

机构信息

School of Engineering & Technology, China University of Geosciences, Beijing 100083, China.

出版信息

Int J Environ Res Public Health. 2021 Dec 21;19(1):38. doi: 10.3390/ijerph19010038.

DOI:10.3390/ijerph19010038
PMID:35010306
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8751000/
Abstract

To scientifically and quantitatively evaluate the degree of urban storm resilience and improve the level of urban stormwater resilience, based on the resilience theory, starting from the three attributes of resilience (resistance, recovery and adaptability), this paper establishes the framework of urban resilience evaluation indicator system under the background of stormwater disaster. Firstly, the weight of the indicator system is analyzed by the Delphi method and cloud model, and then the urban stormwater recilience evaluation model is constructed by using the cloud model and approximate ideal solution ranking method. Through the fuzzy description, the corresponding quantitative value is given to the qualitative indicator, so that the stormwater resilience of the city can be measured by accurate values. Finally, the feasibility of the model is verified by case analysis. The results show that the urban stormwater resilience evaluation theory and method based on cloud model and approximate ideal solution ranking method have important guiding significance to improve the level of urban stormwater resilience.

摘要

为了科学、定量地评价城市雨洪韧性程度,提高城市雨洪韧性水平,本文基于韧性理论,从韧性(抵抗力、恢复力和适应力)的三个属性出发,建立了暴雨灾害背景下城市韧性评价指标体系框架。首先,运用德尔菲法和云模型对指标体系的权重进行分析,然后采用云模型和逼近理想解排序法构建城市雨洪韧性评价模型。通过模糊描述,对定性指标赋予相应的定量值,从而可以用准确数值来衡量城市的雨洪韧性。最后,通过案例分析验证了模型的可行性。结果表明,基于云模型和逼近理想解排序法的城市雨洪韧性评价理论和方法对提高城市雨洪韧性水平具有重要的指导意义。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/107a/8751000/635b570343f1/ijerph-19-00038-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/107a/8751000/22fc66d0ac38/ijerph-19-00038-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/107a/8751000/635b570343f1/ijerph-19-00038-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/107a/8751000/22fc66d0ac38/ijerph-19-00038-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/107a/8751000/635b570343f1/ijerph-19-00038-g002.jpg

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