包容性检验和PCA相融合的物流需求预测  

Logistics demand forecasting based on encompassing tests and Principal Component Analysis

作　　者：蒋梦莉[1] 

机构地区：[1]西安财经学院管理学院信息与物流管理系,西安710100

出　　处：《计算机工程与应用》2013年第15期263-266,270,共5页Computer Engineering and Applications

基　　金：陕西省管理科学与工程重点学科建设专项资金资助项目;陕西省自然科学基金(No.2009JM9008);陕西省教育厅科学研究计划项目(No.09JK437)

摘　　要：模型选择以及如何进行组合是物流需求组合预测的关键,为了提高物流需求的预测精度,提出一种包容性检验和主成分分析相融合的物流需求预测模型(ET-PCA)。采用多个单一模型对物流需求进行预测,采用包容性检验选择最合理的单一模型,利用PCA对选择的单一模型预测结果进行组合,采用仿真实验对组合模型性能进行测试。结果表明,相对于传统组合模型,ET-PCA较好地解决了物流需求单一预测模型选择及组合问题,更加全面、准确描述了物流需求复杂的变化趋势,提高了物流需求的预测精度和效率,具有一定应用价值。Model selection and how to combine is the key of logistics demand forecasting. In order to improve the forecasting accuracy of logistics demand, a logistics dern＇and forecasting model is proposed based on Encompassing Tests and Principal Component Analysis （ET-PCA）. Some single models are used to forecast the logistics demand, and then encompassing tests are used to select good single model. The selected single models are combined by PCA, and the simulation experiment is carried out to test the performance of the combination model on logistics demand data. The simulation results show that, compared with＇ tra- ditional combination model, ET-PCA has solved the problem of how to select and combine the forecasting models. It can be more comprehensive, accurately describe the change trend of logistics demand, and improve the prediction accuracy of logistics demand. It has a good application value.

关 键 词：物流需求 主成分分析 包容性检验 组合模型 

分 类 号：TB24[一般工业技术—工程设计测绘]