大地测量与地球动力学2026，Vol.46Issue(1)：86-93,8.DOI:10.14075/j.jgg.2025.01.011
基于PSO-SVM-SST模型的地震应急物资需求预测研究
Earthquake Emergency Eupplies Demand Forecasting Based on PSO-SVM-SST Model
摘要
Abstract
A post-earthquake affected population prediction model based on support vector machines(SVM)optimized by particle swarm optimization(PSO)is established,and the SST(safety stock theory)earthquake emergency supply demand prediction model is constructed.Nine indicator parame-ters,including seismic hazard and damage severity,are selected and processed through dimensionality reduction and redundancy removal as input variables for the PSO-optimized SVM model to predict the affected population.Based on the relationship between the affected population and emergency supplies in disaster areas,the SST model is applied to indirectly estimate the quantities of typical supplies re-quired in the immediate aftermath of the Jiuzhaigou earthquake.The experimental results are as fol-lows:By employing an error comparison analysis method to validate the model's effectiveness,the PSO-SVM model demonstrates a 14.27％reduction in prediction error compared to the SVM model,with a significant improvement in prediction accuracy.The estimated demand for typical supplies in the aftermath of the Jiuzhaigou earthquake provides a certain degree of reference,indicating that the PSO-SVM-SST prediction model possesses both theoretical and practical rationality and utility.关键词
地震应急物资/需求预测/支持向量机/安全库存理论Key words
earthquake emergency supplies/demand forecasting/support vector machine(SVM)/safety stock theory分类
天文与地球科学引用本文复制引用
唐彦东,程梅,刘军,于汐,林浩..基于PSO-SVM-SST模型的地震应急物资需求预测研究[J].大地测量与地球动力学,2026,46(1):86-93,8.基金项目
河北省教育厅研究生教育教学改革研究项目(YJG2023120) （YJG2023120）
国家重点研发计划(2022YFC3004405). （2022YFC3004405）
