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突发事件一旦发生，应急物资需求种类是纷繁复杂的，应急物流中的物资需求又是紧迫的、动态变化的. 为了提高应急物流的运作效率，救援管理人员需要对应急物资进行分级. 本文提出一种基于后验概率支持向量机的应急物资分类方法，并在此基础上建立应急物资分类模型. 把物资的重要性、时效性和缺口程度三个因素作为物资需求分级的评价标准，将模糊化后的评价值作为PPSVM的输入，选择后验概率最大所的类别作为测试样本的类别输出来完成整个分类过程，从而得到对应的分级结果. 实验结果表明，PPSVM用于应急物资分类是可行的，能够很好地解决应急物资的分类问题.

Emergency Materials Classification Method Based on Posterior Probability Support Vector Machine

Once enlergency happened,the requirements for materials are numerous and complicated,the requirements are urgent and variational as well in.To impove the efficiency of emergency logistics,the rescuer need to classify the emergency materials.A novel method for emergency materials classification based on posterior probability support vector machine is proposed.The classification model for emergency materials is presented via PPSVM.This article took the materials importance;urgency and scarcity as the classified criterion,put the velues after being fuzzed as the input of PPSVM,selected the classification which is corresponding with the Max Posterior Probability as the output ,the results of the classification are obtained finally .Experimental results demonstrate that the proposed method is feasible,it can solve the problem of emergency materials classification effectively.