ARIMA-SVM的物流需求预测模型Logistics demand forecasting model based on ARIMA-SVM
杨建成
摘要(Abstract)：
物流需求是多种因素综合作用的结果,具有规律性和特殊性,变分十分复杂,导致当前物流需求预测模型的预测效果差,难以满足物流管理的实际应用要求。为了解决物流需求建模过程中存在的难题,提出基于ARIMA-SVM的物流需求预测模型。首先对当前物流需求预测的研究现状进行分析,找到引起物流需求预测效果的原因;然后选择差分自回归滑动平均模型对物流需求的规律性变化特点进行建模,支持向量机对物流需求的特殊性变化特点进行建模;最后采用权值方式确定物流需求预测的预测结果,并采用物流需求的预测实例分析模型的有效性。结果表明,ARIMA-SVM的物流需求预测结果要优于当前其他物流需求预测模型,为其他预测问题提供了一种建模工具。
关键词(KeyWords)： 物流管理;随机性变化特点;ARIMA-SVM;权值的确定;预测模型;支持向量机
基金项目(Foundation):
作者(Author): 杨建成
DOI: 10.16652/j.issn.1004-373x.2018.09.040
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