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基于连续区间灰数Verhulst模型的地震救援药品需求预测研究
Study on Drug Demand Forecasting Based on Interval Grey Number Verhulst Model During Post-earthquake
【摘要】 针对地震灾害初期的伤病员人数呈现"S"形变化及其是一个动态连续变化过程的特性,通过信息分解法对连续区间灰数进行标准化处理,将区间灰数分解为白部序列和灰部序列,进而构建连续区间灰数Verhulst动态预测模型.并用该模型预测地震灾害救援初期一定时间间隔的伤病员人数区间变化情况,结合地震灾害伤病员人数变化与紧急救援药品需求间的线性关系,实现对地震灾害救援初期的紧急救援药品需求量的预测.并以青海玉树地震为实例对模型进行检验,实验结果显示预测模型应用的正确性与合理性.
【Abstract】 Since the number of the wounded after earthquake disaster changes following the "S" shape and its dynamic continuity,we try to standardize the continuous interval grey numbers using Information Decomposition Method.The interval gray numbers is divided into white part sequence and Ash Division Series,and constructing a continuous interval gray number Verhulst dynamic forecasting model.Then we analyze and forecast interval changes of the wounded figures at a certain time interval in the initial earthquake rescue,combined with the liner relation between the change numbers of wounded and the emergency drug demand,and bring about the prediction of emergency drug demand in the initial earthquake rescue.Also we take Yushu earthquake in Qinghai as an example to test the model,and the experiment proving the correctness and rationality of its applying..
- 【文献出处】 数学的实践与认识 ,Mathematics in Practice and Theory , 编辑部邮箱 ,2015年07期
- 【分类号】O242.1
- 【被引频次】1
- 【下载频次】101