Journal of Dalian Maritime University >
2020 , Vol. 46 >Issue 1: 107 - 113
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2020.01.012
Prediction of China coastal bulk freight index based on EEMD-PSO-LSSVM
Received date: 2019-09-05
Revised date: 2019-11-02
Online published: 2019-11-02
To meet the requirement of China coastal bulk freight index (CBFI) prediction accuracy, from the perspective of internal fluctuation characteristics, a combined prediction model based on ensemble empirical mode decomposition (EEMD)-particle swarm optimization (PSO)-least squares support vector machine (LSSVM) was proposed. The comparison of three prediction models of LSSVM, PSO-LSSVM and EMD-PSO-LSSVM shows that EEMD can decompose and denoise the data with large fluctuation in CBFI sequence to reserve the inherent fluctuation characteristics of the sequence. Moreover, the prediction accuracy is improved to a certain extent, and the prediction performance is better.
JIA Hong-yu , ZHOU Chen-xin , WANG Yu-han , LIN Yan . Prediction of China coastal bulk freight index based on EEMD-PSO-LSSVM[J]. Journal of Dalian Maritime University, 2020 , 46(1) : 107 -113 . DOI: 10.16411/j.cnki.issn1006-7736.2020.01.012
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