交通运输系统工程与信息

交通运输系统工程与信息 ›› 2011, Vol. 11 ›› Issue (3): 50-57.

• 系统工程理论与方法 • 上一篇    下一篇

基于支持向量机的巴拿马型船舶运价指数预测方法

杨忠振*1，靳廉洁1,2，王明华1   

  1. 1. 大连海事大学 交通运输管理学院, 辽宁大连 116026; 2. 交通运输部规划研究院，北京 100028
  • 收稿日期:2011-03-02 修回日期:2011-04-12 出版日期:2011-06-25 发布日期:2011-07-18
  • 作者简介:杨忠振（1964-），男，辽宁凌海人，教授，博士生导师，博士.

Forecasting Baltic Panamax Index with Support Vector Machine

YANG Zhong-zhen1, JIN Lian-jie1,2, WANG Ming-hua1   

  1. 1. Transportation Management College, Dalian Maritime University, Dalian 116026, Liaoning, China;2. Transportation Planning and Research Institute, Ministry of Transport, Beijing 100028, China
  • Received:2011-03-02 Revised:2011-04-12 Online:2011-06-25 Published:2011-07-18

被引次数

20

摘要： 考察运价指数波动的内在规律和外在影响，提出新模型预测运价指数，为航运市场经营者和投资者提供把握市场态势、规避价格风险的有力工具. 针对波罗的海巴拿马型船舶运价指数（BPI）序列，首先用小波变换对运价指数序列进行去噪，消除干散货运输市场中无规律的突发事件所造成的影响；在此基础上以前五个月的BPI值为输入变量，以第六个月的运价指数为输出变量，对支持向量机（SVM）进行训练，得到预测模型. 通过实证分析发现小波变换-SVM混合预测模型具有较高的预测精度，可用于对巴拿马船型运价走势的预测.

关键词: 水路运输, 交通运输经济, 支持向量机(SVM), 小波变换, 运价指数, 预测

Abstract: This paper develops a model to forecast the freight index through studying the internal mechanism and the external influence factors. The model can provide a powerful tool for the operators and investors to understand the market trend and avoid the price risk. By taking the freight index of Panamax bulk carriers as subject, firstly, in order to eliminate the impact of random incidents in dry bulk market, wavelet transform is adopted to de-noise the Baltic Panamax Index (BPI). Then, the wavelet transform and Support Vector Machine (SVM) combined model to predict BPI is established. The inputs of the model are the values of the five prior consecutive monthly BPI, and the output is the sixth monthly BPI. The model and the forecasted results are obtained through SVM training. Finally, the numerical analysis shows that the wavelet transform and SVM combined model has higher accuracy and can be used to predict the trend of the freight rates of the Panamax bulk carriers.

Key words: waterway transportation, transportation economy, Support Vector Machine (SVM), wavelet transform, Baltic Panamax Index (BPI), forecasting

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