人民长江2024，Vol.55Issue(2)：26-34,9.DOI:10.16232/j.cnki.1001-4179.2024.02.004
基于BP神经网络的洪涝灾害承灾体脆弱性评估
Assessment on vulnerability of flood disaster bearing body based on BP neural network
摘要
Abstract
To reduce the damage of flood disasters to the bearing body,Beijing City as an example,an assessment framework for vulnerability of flood disaster bearing body considering exposure,sensitivity and adaptive capacity was developed.The entropy-weighted TOPSIS algorithm was applied to objectively weight the vulnerability indicators of flood disaster bearing body and obtain the standardized vulnerability index.The initial weights and vulnerability indices were used as input and output datasets,respec-tively,for training a BP neural network to obtain optimized weights.Furthermore,the ArcGIS technique was combined to assess the vulnerability of flood disaster bearing body,and the natural break method was used to classify the vulnerability into 4 levels.The results showed that:①Population density,economic density,urban POI density,vegetation coverage and drainage pipe network sig-nificantly influenced the vulnerability of flood disaster bearing body in Beijing City.②The vulnerability of flood disaster bearing body in Beijing city gradually decreased from southeast to northwest in spatial distribution,with higher vulnerability levels in the central urban area and lower vulnerability levels in the peripheral areas.The research results have certain guiding significance for reducing the vulnerability of flood disaster bearing body in Beijing City,and the weight optimization model and vulnerability as-sessment model can also be applied to the other cities.关键词
洪涝灾害/承灾体脆弱性/熵权法/TOPSIS/BP神经网络/ArcGIS/北京市Key words
flood disasters/vulnerability of disaster bearing body/entropy weight method/TOPSIS/BP neural network/ArcGIS/Beijing City分类
建筑与水利引用本文复制引用
袁旭山,刘京会,宋珂..基于BP神经网络的洪涝灾害承灾体脆弱性评估[J].人民长江,2024,55(2):26-34,9.基金项目
国家自然科学基金项目(72174019) （72174019）
