灾害学2025，Vol.40Issue(4)：31-36,6.DOI:10.3969/j.issn.1000-811X.2025.04.006
基于PCA-BP神经网络的应急响应物资精准需求预测模型构建
Construction of a Precise Demand Prediction Model for Emergency Supplies Based on PCA-BP Neural Network:A Case Study of Survivors'Living Material Needs in the Initial Phase of Earthquake Disaster Response
摘要
Abstract
To enhance disaster emergency response capabilities,achieve precise supply of emergency materi-als in the initial response phase,and ensure the basic living needs of disaster victims,we take examples from cer-tain earthquake disasters in China,collect seismic data,and use the number of people in need of emergency relo-cation as the prediction target.Relevant seismic indicators are selected as influencing factors and a predictive model is constructed for the number of emergency relocation individuals based on Principal Component Analysis(PCA)and Back Propagation(BP)neural networks.Based on this,a material demand forecasting model is es-tablished by integrating the relationship between the number of people requiring emergency relocation and the material needs of disaster victims.The results indicate that this model possesses higher accuracy in predicting emergency relocation populations and can estimate the number of individuals requiring emergency relocation quite accurately.Furthermore,in terms of predicting material needs,validation through case studies demonstrates that the model has practical value and can provide a scientific basis for material allocation decisions in the initial phase of emergency response.关键词
应急响应/需求预测/地震/主成分分析法(PCA)/反向(BP)神经网络Key words
emergency response/demand prediction/earthquake/Principal Component Analysis(PCA)/backpropagation(BP)neural network分类
资源环境引用本文复制引用
李尧远,曲政澍..基于PCA-BP神经网络的应急响应物资精准需求预测模型构建[J].灾害学,2025,40(4):31-36,6.基金项目
国家社会科学基金项目"突发公共卫生事件精准应急响应机制研究"(22BZZ091) （22BZZ091）
