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[1]张颖,杨晓婷,韩业凡,等.暴雨洪涝灾害转移安置人数的组合预测模型研究*[J].中国安全生产科学技术,2024,20(3):172-180.[doi:10.11731/j.issn.1673-193x.2024.03.024]
　ZHANG Ying,YANG Xiaoting,HAN Yefan,et al.Study on combined prediction model for number of transferred and resettled people in rainstorm-flood disaster[J].JOURNAL OF SAFETY SCIENCE AND TECHNOLOGY,2024,20(3):172-180.[doi:10.11731/j.issn.1673-193x.2024.03.024]
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暴雨洪涝灾害转移安置人数的组合预测模型研究*
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《中国安全生产科学技术》[ISSN:1673-193X/CN:11-5335/TB]

卷:
20
期数:
2024年3期
页码:
172-180
栏目:
职业安全卫生管理与技术
出版日期:
2024-03-31

文章信息/Info

Title:
Study on combined prediction model for number of transferred and resettled people in rainstorm-flood disaster
文章编号:
1673-193X(2024)-03-0172-09
作者:
张颖; 杨晓婷; 韩业凡; 吕伟; 房志明
（1.武汉理工大学 安全科学与应急管理学院，湖北 武汉 430070；
2.上海理工大学 管理学院，上海 200093）
Author(s):
ZHANG Ying;  YANG Xiaoting;  HAN Yefan;  LYU Wei;  FANG Zhiming
(1.School of Safety Science and Emergency Management,Wuhan University of Technology,Wuhan Hubei 430070,China;
2.Business School,University of Shanghai for Science and Technology,Shanghai 200093,China)
关键词:
暴雨洪涝灾害; 转移安置人数; 组合预测; 支持向量机（SVM）
Keywords:
rainstorm-flood disaster;  number of transferred and resettled people;  combined prediction;  support vector machines (SVM)
分类号:
X915.5；X913.4
DOI:
10.11731/j.issn.1673-193x.2024.03.024
文献标志码:
A
摘要:
为了更加科学精准地预测暴雨洪涝灾害下需要转移安置的人数，收集2011—2018年全国范围内严重暴雨洪涝灾害案例，通过Pearson 相关性分析检验转移安置人数与表征暴雨洪涝灾害严重程度影响因素之间的关系；分别使用基于主成分分析的回归模型和支持向量机（SVM）预测暴雨洪涝灾害下需要转移安置人数，并以2种方法的结果为基础，提出1种组合预测方法对暴雨洪涝灾害转移人数进行修正。研究结果表明：组合预测法的MSE、MAE均小于回归预测和SVM模型预测。使用组合预测方法对洪涝灾害转移安置人数进行预测，可以充分结合单一预测模型的优势，提高组合预测模型的预测精度和泛化能力。研究结果可为确定暴雨洪涝灾害的避难需求并制定避难疏散计划提供参考。
Abstract:
In order to predict the number of people who need to be transferred and resettled under the rainstorm-flood disasters more scientifically and accurately,the cases of severe rainstorm-floods in China from 2011 to 2018 were collected,and the relationship between the number of transferred and resettled people and the influencing factors representing the severity of rainstorm-flood disaster was tested by Pearson correlation analysis.Then,the regression model based on principal component analysis (PCA) and the support vector machines (SVM) were used to predict the number of people who need to be transferred and resettled under rainstorm-flood disaster.Based on the results of the two methods,a combined prediction method was proposed to revise the number of transferred and resettled people under rainstorm-flood disaster.The results show that both the MSE and MAE of the combined prediction method are less than those of regression prediction and SVM model prediction.Using the combined prediction method to predict the number of transferred and resettled people in flood disaster can fully combine the advantages of single prediction model and improve the prediction accuracy and generalization ability of the combined prediction model.The research results can provide a reference for determining the sheltering needs of rainstorm-flood disasters and formulating the sheltering evacuation plans.

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备注/Memo

备注/Memo:
收稿日期： 2023-08-04；网络首发日期： 2024-03-19
* 基金项目： 国家自然科学基金项目(52072286)
作者简介： 张颖，博士研究生，主要研究方向为城市公共安全与应急管理。
通信作者： 杨晓婷，博士研究生，主要研究方向为城市公共安全与应急管理。
更新日期/Last Update: 2024-04-07