Prediction of BDI based on VMD-FFT-LSTM model

  • WU Hua-hua ,
  • KUANG Hai-bo ,
  • SONG Yang
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  • (a. Collaborative Innovation Center for Transport Studies;b. Transportation Engineering College,Dalian Maritime University, Dalian 116026, China)

Received date: 2019-01-31

  Revised date: 2019-05-15

  Online published: 2019-05-15

Abstract

To improve the prediction effect of non-linear BDI, the single-step and multi-step prediction results of various prediction models for BDI index were analyzed,and the VMD-FFT-LSTM combination prediction model was constructed based on the idea of "decomposition-reconstruction-prediction". Firstly, IMF components of BDI were decomposed by using VMD algorithm. Then, the IMF was reconstructed based on the BDI exponential cycle theory and the periodic results calculated by the FFT algorithm to achieve the purpose of noise reduction. Finally, the LSTM model was used for multi-step prediction of reconstruction sequences. Compared with the multi-step prediction results, it was shown that the prediction results of the VMD-FFT-LSTM combined model have better accuracy and stability,which solved the limitation of SVR model that the multi-step prediction results are prone to large deviation at the local extreme points of the sequence.

Cite this article

WU Hua-hua , KUANG Hai-bo , SONG Yang . Prediction of BDI based on VMD-FFT-LSTM model[J]. Journal of Dalian Maritime University, 2019 , 45(3) : 9 -16 . DOI: 10.16411/j.cnki.issn1006-7736.2019.03.002

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