港口吞吐量的典型因素预测模型
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摘要
港口吞吐量的预测受众多因素的影响,如何确定影响港口吞吐量的典型因素,是预测的关键问题之一。为解决此关键问题,先对港口吞吐量影响因素进行分析,再用系统聚类法确定其中的典型因素。以典型因素作为自变量,应用多元线性回归分析法建立港口吞吐量的典型因素预测模型。对厦门港集装箱吞吐量的预测结果表明,该模型有较高的拟合度和预测精度。
The prediction of port throughput is influenced by many factors,and how to determine its typical influencing factors is one of the key problems in forecasting. In order to solve this key problem,the influencing factors of port throughput are analyzed,and the systematic clustering method is used to determine the typical factors in the influencing factors. Taking the typical factors as independent variables,the multiple linear regression analysis method is adopted to establish a model of typical factor prediction on port throughput. The prediction results of Xiamen Port container throughput show that the model is of higher fitting degree and prediction accuracy.
The prediction of port throughput is influenced by many factors,and how to determine its typical influencing factors is one of the key problems in forecasting. In order to solve this key problem,the influencing factors of port throughput are analyzed,and the systematic clustering method is used to determine the typical factors in the influencing factors. Taking the typical factors as independent variables,the multiple linear regression analysis method is adopted to establish a model of typical factor prediction on port throughput. The prediction results of Xiamen Port container throughput show that the model is of higher fitting degree and prediction accuracy.
引文
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[3]戴霖,黄浩,黄倩盈,等.基于马尔科夫模型的港口吞吐量预测[J].水运管理,2014,36(3):18-22.DOI:10.13340/j.jsm.2014.03.005.
[4]范莹莹,余思勤.基于NARX神经网络的港口集装箱吞吐量预测[J].上海海事大学学报,2015,36(4):1-5.DOI:10.13340/j.jsmu.2015.04.001.
[5]朱小檬,栾维新,朱义胜.基于时间序列-因果关系结合法的中国海港集装箱吞吐量中长期预测[J].大连海事大学学报(社会科学版),2014,13(5):1-5.
[6]XIE Gang,WANG Shouyang,ZHAO Yingxue,et al.Hybrid approaches based on LSSVR model for container throughput forecasting:a comparative study[J].Applied Soft Computing,2013,13(5):2232-2241.
[7]GENG Jing,LI Mingwei,HONG Weichiang,et al.Port throughput forecasting by using PPPR with chaotic efficient genetic algorithms and CMA[C]//2015 IEEE International Conference on Systems,Man,and Cybernetics.Kowloon,China,9-12 Oct 2015.IEEE,2015:1633-1638.DOI:10.1109/SMC.2015.288.
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[9]韩明.应用多元统计分析[M].上海:同济大学出版社,2013.
[10]林连.厦门港集装箱吞吐量预测研究[D].武汉:武汉理工大学,2009.
[11]姚天祥,巩在武.灰色预测理论及其应用[M].北京:科学出版社,2014.