SVM在九江港吞吐量预测中的应用研究  

Application of SVM Model in the Prediction of Harbor Handling Capacity in Jiujiang

作　　者：程文忠[1] 任凤香[1] 周宣赤[2] 

机构地区：[1]江西财经职业学院,江西九江332000 [2]北京理工大学,北京100081

出　　处：《物流工程与管理》2012年第9期61-64,共4页Logistics Engineering and Management

摘　　要：港口吞吐量预测是港口发展建设的重要依据,正确预测港口吞吐量可促使港口持续健康发展。SVM模型可以在信息量少、数据不完全情况下预测港口吞吐量的发展变化,预测精度高。针对九江港口码头吞吐量进行预测,提出基于支持向量机(Support Vector Machine,SVM)理论的港口码头吞吐量预测模型,将港口吞吐量分别从一般货物与集装箱两类进行分析后,再统一预测港口总吞吐量的趋势,并以九江港口为例,对模型进行实例分析,验证了模型的可行性,预测结果数据清晰,为相关政策制定提供参考。The prediction of harbor handling capacity is an important basis for the construction of port development,and correctly predicting harbor handling capacity may promote the port to develop sustainedly and healthily.The SVM model can predict the development and change of port with accuracy in less information,incomplete data situation In connection with the prediction of harbor handling capacity in Jiujiang,this paper puts forward the prediction model of harbor handling capacity which is based on support vector machine（SVM）.It predicts the trend of the total harbor handling capacity after analysis of general cargo and container,This paper takes Jiujiang port for example to verify the feasibility of the model.The results of data is clear,which provides a reference for the relevant policy formulation

关 键 词：支持向量机 九江港 吞吐量 预测 

分 类 号：F550[经济管理—产业经济]