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基于XGBoost的震后物资动态需求预测

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地震作为突发性自然灾害,常常造成严重人员伤亡,应急物资需求预测研究是灾后应急救援的重要组成部分,是物资统筹调配的前提,合理科学的物资需求预测可以提高救援效率.针对震后应急物资需求预测分为两步,首先,对震灾总伤亡人数进行预计,再利用经验函数对地震动态伤亡人数进行初始估计;旨在根据前期时间段内的伤亡人数,实现对后续伤亡人数有更为精准的预测,将以前序时间内的伤亡人数为依据,引入基于XG-Boost的地震动态伤亡人数预测模型,以提高预测的准确性和可靠性.其次,利用物资需求量与动态伤亡人数的线性关系,根据具有提前期概念的动态需求估计模型计算出每日所需物资,实现动态需求预测.最后,运用所提方法对"汶川地震"伤亡人数、受伤人数、死亡人数进行动态预测,并估算了物资动态需求量,为灾区应急物资供应提供参考.
Post-Earthquake Material Dynamic Demand Forecast Based on XGBoost
As a sudden natural disaster,earthquake often causes serious casualties,and the research on emergency material de-mand prediction is an important part of post-disaster emergency rescue,and it is the premise of overall material allocation.This pa-per divides the prediction of the demand for emergency supplies after the earthquake into two steps:firstly,the total number of casu-alties of the earthquake is estimated,and then the empirical function is used to estimate the initial number of earthquake casualties,and the purpose is to achieve a more accurate prediction of the subsequent casualties according to the casualties in the previous peri-od of time,and the XGBoost-based seismic dynamic casualties prediction model is introduced based on the casualties in the previous time to improve the accuracy and reliability of the prediction.Secondly,the linear relationship between the material demand and the number of dynamic casualties is used to calculate the daily material demand according to the dynamic demand estimation model with the concept of lead time,so as to realize the dynamic demand forecasting.Finally,the proposed method is used to dynamically pre-dict the number of casualties,injuries and deaths of the"Wenchuan earthquake",and the dynamic demand for materials is esti-mated,which provides a reference for the supply of emergency materials in the disaster area.

earthquake disastercasualty forecastXGBoostlead timedemand estimation model

李艳、徐慧颖、周鑫鑫、王付宇

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安徽工业大学 管理科学与工程学院,安徽 马鞍山 243032

复杂系统多学科管理与控制安徽普通高校重点实验室,安徽 马鞍山 243002

地震灾害 人员伤亡预测 XGBoost 提前期 需求估计模型

2024

黑龙江工业学院学报(综合版)
鸡西大学

黑龙江工业学院学报(综合版)

影响因子:0.211
ISSN:1672-6758
年,卷(期):2024.24(8)