基于新陈代谢GM(1,1)的大规模地震应急救援物资需求预测研究
|
摘要
大规模地震发生后,在时间有限且信息缺乏的情况下,以大样本为建模基础构建的传统预测模型难以实现对应急救援物资的快速准确预测。基于此,以灰色建模理论为基础,提出并构建一种基于新陈代谢的GM(1,1)灰色动态预测模型,利用其"去掉老信息,利用新信息"的建模特性,分析并预测地震灾区死亡人数的动态变化,进而预测相应地应急救援物资需求。将该模型应用于预测我国青海玉树地震灾区物资需求的数量,取得了较好的预测效果。研究成果对丰富与完善灰色预测模型的理论体系,实现大规模地震灾区应急救援物资需求的预测,具有重要的理论意义和应用价值。
In the case of limited time and lack of information after large-scale earthquakes,a fast and accurate prediction of emergency relief supplies is hard to be achieved by traditional forecasting models based on large samples.The gray modeling theory proposes and constructs the metabolism of gray dynamic prediction model based on GM(1,1),according to its modeling features of removing the old information and using the new information,analysing and forecasting dynamic changes of the number of deaths in the earthquake-stricken areas,and thus predicting the corresponding emergency relief supplies needs.The model used to predict the quantity of the material needs of Yushu earthquake in Qinghai obtains a better prediction.Important theoretical significance and application value are provided for enriching and improving gray prediction model of the theoretical system,satisfying forecasting demand of emergency relief supplies in large-scale earthquake-stricken areas.
In the case of limited time and lack of information after large-scale earthquakes,a fast and accurate prediction of emergency relief supplies is hard to be achieved by traditional forecasting models based on large samples.The gray modeling theory proposes and constructs the metabolism of gray dynamic prediction model based on GM(1,1),according to its modeling features of removing the old information and using the new information,analysing and forecasting dynamic changes of the number of deaths in the earthquake-stricken areas,and thus predicting the corresponding emergency relief supplies needs.The model used to predict the quantity of the material needs of Yushu earthquake in Qinghai obtains a better prediction.Important theoretical significance and application value are provided for enriching and improving gray prediction model of the theoretical system,satisfying forecasting demand of emergency relief supplies in large-scale earthquake-stricken areas.
引文
[1]王晓,庄亚明.基于案例推理的非常规突发事件资源需求预测[J].华东经济管理,2011,25(01):115-117.
[2]高惠瑛,李清霞.地震人员伤亡快速评估模型研究[J].灾害学,2010,25:275-277.
[3]周露,陈曦,陈宏,等.应急状态下救灾物资供给特点研究—以汶川地震食品供给为例[J].管理评论,2008,20(12):25-29.
[4]刘思峰,党耀国,方志耕,等.灰色系统理论及其应用[M].北京:科学出版社,2010.
[5]党耀国,刘思峰,王正新,等.灰色预测与决策模型研究[M].北京:科学出版社,2009.
[6]SHEU J-B.An emergency logistics distribution approach for quick response to urgent relief demand in disasters[J].Transportation Research Part E,2007,43:687-709.
[7]马玉宏,谢礼立.地震人员伤亡估算方法研究[J].地震工程与工程振动,2000,20(4):140-147.
[8]何明哲,周文松.基于地震损伤指数的地震人员伤亡预测方法[J].哈尔滨工业大学学报,2011,43(4):23-27.
[9]王宗喜,徐东,黄定政.关于应急物流规划的几点思考[J].中国流通经济,2010,(6):20-22.
[10]宋传平.我国应急物流系统的构建和保障条件[J].中国流通经济.2011,(04):21-24.
[11]谢乃明,刘思峰.一类离散灰色模型及其预测效果研究[J].系统工程学报,2006,21(5):520-523.
[12]谢乃明,刘思峰.离散灰色模型的拓展及其最优化求解[J].系统工程理论与实践,2006,26(6):108-112.
[13]邓聚龙.灰色系统基本方法[M].武汉:华中科技大学出版社,2005.
[14]田刚,李南,刘思峰.基于参数优化的物流需求灰预测研究[J].华东经济管理,2011,25(06):155-157.
[15]吴红英,魏利胜.倒立摆网络控制系统的自适应灰色预测策略研究[J].计算机科学,2010,37(2):253-255.
[2]高惠瑛,李清霞.地震人员伤亡快速评估模型研究[J].灾害学,2010,25:275-277.
[3]周露,陈曦,陈宏,等.应急状态下救灾物资供给特点研究—以汶川地震食品供给为例[J].管理评论,2008,20(12):25-29.
[4]刘思峰,党耀国,方志耕,等.灰色系统理论及其应用[M].北京:科学出版社,2010.
[5]党耀国,刘思峰,王正新,等.灰色预测与决策模型研究[M].北京:科学出版社,2009.
[6]SHEU J-B.An emergency logistics distribution approach for quick response to urgent relief demand in disasters[J].Transportation Research Part E,2007,43:687-709.
[7]马玉宏,谢礼立.地震人员伤亡估算方法研究[J].地震工程与工程振动,2000,20(4):140-147.
[8]何明哲,周文松.基于地震损伤指数的地震人员伤亡预测方法[J].哈尔滨工业大学学报,2011,43(4):23-27.
[9]王宗喜,徐东,黄定政.关于应急物流规划的几点思考[J].中国流通经济,2010,(6):20-22.
[10]宋传平.我国应急物流系统的构建和保障条件[J].中国流通经济.2011,(04):21-24.
[11]谢乃明,刘思峰.一类离散灰色模型及其预测效果研究[J].系统工程学报,2006,21(5):520-523.
[12]谢乃明,刘思峰.离散灰色模型的拓展及其最优化求解[J].系统工程理论与实践,2006,26(6):108-112.
[13]邓聚龙.灰色系统基本方法[M].武汉:华中科技大学出版社,2005.
[14]田刚,李南,刘思峰.基于参数优化的物流需求灰预测研究[J].华东经济管理,2011,25(06):155-157.
[15]吴红英,魏利胜.倒立摆网络控制系统的自适应灰色预测策略研究[J].计算机科学,2010,37(2):253-255.
版权所有：© 2023 中国地质图书馆 中国地质调查局地学文献中心