基于GGRA-GPR模型的洪涝灾害直接经济损失预评估  被引量:1

Pre-assessment of Direct Economic Losses of Flood Disasters Based on GGRA-GPR Model

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作  者:杨爽 薛晔[1] YANG Shuang;XUE Ye(College of Economics and Management,Taiyuan University of Technology,Taiyuan 030024,China)

机构地区:[1]太原理工大学经济管理学院,山西太原030024

出  处:《水电能源科学》2023年第10期67-71,共5页Water Resources and Power

基  金:教育部人文社会科学研究规划基金项目(20YJAZH116);国家社会科学基金一般项目(20BSH128)。

摘  要:随着经济发展及洪涝灾害频率和强度的增加,灾后应急管理需快速了解灾害损失,需先从致灾因子、承灾体、孕灾环境、应急能力、灾情等5个方面构建指标体系,并基于广义灰色关联分析验证其合理性,其次引入高斯过程回归模型对洪涝灾害经济损失进行预评估模拟,最后运用该方法评估了京津冀城市群2010~2020年洪涝灾害直接经济损失。结果表明,对比单纯高斯过程回归与神经网络评估模型,广义灰色关联分析—高斯过程回归模型具有最优的拟合精度。With the increase of economic development and the frequency and intensity of flood disasters,post-disaster emergency management requires rapid understanding of disaster losses.This paper firstly constructed an index system from five aspects including disaster-causing factors,disaster-bearing bodies,disaster-pregnant environment,emergency response capacity and disaster situation,and verified its rationality based on generalized gray correlation analysis.Secondly,Gaussian process regression model was introduced to pre-evaluate and simulate the economic losses of flood disasters.Finally,the method was applied to evaluate the direct economic losses of flood disasters in Beijing-Tianjin-Hebei urban agglomeration from 2010 to 2020.The results show that the generalized gray correlation analysis-Gaussian process regression model has the best fitting accuracy when comparing the simple Gaussian process regression with the neural network assessment model.

关 键 词:洪涝灾害 高斯过程回归模型 广义灰色关联分析 损失预评估 

分 类 号:TV12[水利工程—水文学及水资源] X43[环境科学与工程—灾害防治]

 

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