[1]郭鑫宇,杨敬畏,厉智成,等.主客观组合权重-TOPSIS-k-means++法内涝风险评估[J].中国给水排水,2024,40(5):130-136.
　GUOXin-yu,YANGJing-wei,LIZhi-cheng,et al.Waterlogging Risk Assessment Based on Subjective and Objective Combination Weight-TOPSIS-k-means++[J].China Water & Wastewater,2024,40(5):130-136.
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主客观组合权重-TOPSIS-k-means++法内涝风险评估

中国给水排水[ISSN:1000-4062/CN:12-1073/TU] 卷: 第40卷 期数: 2024年第5期 页码: 130-136 栏目: 出版日期: 2024-03-01
Title:
Waterlogging Risk Assessment Based on Subjective and Objective Combination Weight-TOPSIS-k-means++
作者:
郭鑫宇1， 杨敬畏1， 厉智成1， 王洋1， 程树辉1， 李继选2
（1.北京市市政工程设计研究总院有限公司，北京 100082；2.舞川环境科技<上海>有限公司，上海 201821）
Author(s):
GUO　Xin-yu1， YANG　Jing-wei1， LI　Zhi-cheng1， WANG　Yang1， CHENG　Shu-hui1， LI　Ji-xuan2
（1. Beijing Municipal Engineering Design and Research Institute Co. Ltd.， Beijing 100082， China； 2. Wuchuan Environmental Technology Co. Ltd.， Shanghai 201821， China）
关键词:
内涝风险评估;  TOPSIS;  熵权法;  层次分析法;  k-means++
Keywords:
waterlogging risk assessment;  TOPSIS;  entropy weight method;  analytic hierarchy process;  k-means++
摘要:
内涝风险较高是多数城镇面临的问题。以某感潮城镇片区为例，基于InfoWorks ICM建立的雨水管网-河段一二维耦合模型计算结果，利用地理信息系统（GIS）的栅格分析和邻域分析技术对孕灾环境危险性和易损性指标进行量化，最后运用GIS空间连接功能进行图层叠加。采用耦合熵权法和层次分析法计算各指标的组合权重，积水深度、积水流速、与幼儿园的距离、与医院的距离、GDP密度和人口密度的权重分别为0.365、0.177、0.084、0.088、0.084、0.202。构建基于主客观组合权重-TOPSIS-k-means++的内涝风险评估模型，并与主客观组合权重-加权评分-k-means++方法对比，验证了该方法的有效性。研究结果表明，综合考虑危险性和易损性指标，运用k-means++方法对风险等级进行聚类分析可为片区雨水管渠设计和内涝点整治提供综合性科学依据。
Abstract:
Most towns are facing high risk of waterlogging in China. The risk and vulnerability indicators of a risk-potential environment in a tidal town area were quantified by using grid analysis and neighborhood analysis of geographic information system (GIS), and the layers were overlaid by using GIS spatial connection function based on the calculation results of one-dimensional and two-dimensional coupling model of storm sewer system-river established by InfoWorks ICM. The combination weights of each index were calculated by coupling entropy weight method and analytic hierarchy process, and the weights of waterlogging depth, waterlogging velocity, distance to kindergarten, distance to hospital, GDP density and population density were 0.365, 0.177, 0.084, 0.088, 0.084 and 0.202, respectively. A waterlogging risk assessment model based on subjective and objective combination weight-TOPSIS-k-means++ was constructed, and its calculation results were compared with those of subjective and objective combination weight-weighted score-k-means++ method, which verified the effectiveness of the research method. The application of k-means++ method to cluster the risk level based on comprehensive consideration of risk and vulnerability indicators provides a comprehensive scientific basis for the design of rainwater pipelines and the remediation of waterlogging points in the area.

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更新日期/Last Update: 2024-03-01