上海交通大学学报(自然版) ›› 2013, Vol. 47 ›› Issue (02): 295-299.

• 交通运输 • 上一篇    下一篇

基于小波分析的铁矿石运价预测

赵福杰,谢新连   

  1. (大连海事大学 综合运输研究所, 辽宁 大连 116026)
  • 收稿日期:2011-12-12 出版日期:2013-02-28 发布日期:2013-02-28
  • 基金资助:

    国家自然科学基金项目 (50778029),高等学校博士学科点专项科研基金资助课题(20102125110002)

Forecasting Iron Ore Freight Rates Based on Wavelet Analysis

 ZHAO  Fu-Jie, XIE  Xin-Lian   

  1. (Integrated Transport Institute, Dalian Maritime University, Dalian, Liaoning 116026, China)
  • Received:2011-12-12 Online:2013-02-28 Published:2013-02-28

摘要: 在分析了小波分析对铁矿石海运价格非平稳数据序列预测优势的基础上,介绍了多分辨率分析理论和奇异性检测,借助于MATLAB和EVIEWS软件,建立自回归移动平均(ARMA)和Holt-Winters非季节组合模型,对经过处理的高频和低频数据进行静态和动态预测.预测结果表明,小波分析在非平稳时间序列预测方面具有很大的优势.  

关键词: 铁矿石, 运价预测, 小波分析, 自回归移动平均模型

Abstract: Based on the advantage of the wavelet analysis for non-stationary time series forecasting, this thesis presented multiresolution analysis theory as well as detecting singularity for time series, then made static and dynamic estimation of the processed high and low frequency data by using the autoregressive moving average(ARMA) model and Holt-Winters-No Seasonal with the software of AMTLAB and EVIEWS. The results show that the wavelet analysis in non-stationary time series prediction has a great advantage.

Key words: iron ore, freight rates forecast, wavelet analysis, autoregressive moving average(ARMA) model

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