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大型或者连续型突发事件爆发后,整个应急项目中耗材的合理供给是有效降低财产损失和人员伤亡的关键因素,故深入研究相关的需求预测方法和模型具有重大的理论价值和实际意义。由于突发事件的非同质性与爆发性等特征,导致了应急项目耗材需求数据具备突变性和少样本性,进而导致常用的计量模型和预测方法均无法完全适应。基于此,在结合灰色理论中缓冲算子和灰色GM模型的基础上提出了灰色组合预测模型,缓冲算子解决了突变性问题,灰色组合预测模型解决了贫信息少样本问题,最后通过算例充分说明了组合模型在应急项目耗材预测上的可行性和有效性。
After large or continuous emergencies, the rational supply of consumables in the entire emergency project is a key factor to effectively reduce property losses and casualties. Therefore, it is of great theoretical and practical significance to study the related demand forecasting methods and models in depth. Due to the characteristics of non-homogeneity and explosiveness of emergencies, the demand data of emergent project consumables have the characteristics of mutation and few samples, which leads to the common measurement models and forecasting methods can not be completely adapted. Based on this, a gray combined forecasting model is proposed based on the combination of buffer operator and gray GM model in gray theory. The buffer operator solves the problem of mutation. The gray combined forecasting model solves the problem of poor information less sample. Finally, It fully demonstrates the feasibility and effectiveness of the combined model in predicting the consumables of emergency projects.