Preprints
https://doi.org/10.5194/os-2021-2
https://doi.org/10.5194/os-2021-2
28 Jan 2021
 | 28 Jan 2021
Status: this preprint has been withdrawn by the authors.

An EMD-PSO-LSSVM hybrid model for significant wave height prediction

Gang Tang, Haohao Du, Xiong Hu, Yide Wang, Christophe Claramunt, and Shaoyang Men

Abstract. Accurate and significant wave height prediction with a couple of hours of warning time should offer major safety improvements for coastal and ocean engineering applications. However, significant wave height phenomenon is nonlinear and nonstationary, which makes any prediction simulation a non straightforward task. The aim of the research presented in this paper is to improve predicted significant wave height via a hybrid algorithm. Firstly, empirical mode decomposition (EMD) is used to preprocess the nonlinear data, which are decomposed into several simple signals. Then, least square support vector machine (LSSVM) with nonlinear learning ability is used to predict the significant wave height, and particle swarm optimization (PSO) is implemented to automatically perform the parameter selection in LSSVM modeling. The EMD-PSO-LSSVM model is used to predict the significant wave height for 1, 3 and 6 hours leading times of two stations in the offshore and deep-sea areas of the North Atlantic Ocean. The results show that the EMD-PSO-LSSVM model can remove the lag in the prediction timing of the single prediction models. Furthermore, the prediction accuracy of the EMD-LSSVM model that has not been optimized in the deep-sea area has been greatly improved, an improvement of the prediction accuracy of Coefficient of determination (R2) from 0.991, 0.982 and 0.959 to 0.993, 0.987 and 0.965, respectively, has been observed. The proposed new hybrid model shows good accuracy and provides an effective way to predict the significant wave height for the deep-sea area.

This preprint has been withdrawn.

Gang Tang, Haohao Du, Xiong Hu, Yide Wang, Christophe Claramunt, and Shaoyang Men

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on os-2021-2', Anonymous Referee #1, 01 Mar 2021
    • AC1: 'Reply on RC1', Haohao Du, 06 Mar 2021
  • RC2: '关于 os-2021-2 的评论', Anonymous Referee #2, 29 Mar 2021
    • AC3: 'Reply on RC2', Haohao Du, 21 Apr 2021
  • RC3: 'Comment on os-2021-2', Anonymous Referee #2, 30 Mar 2021
    • AC2: 'Reply on RC3', Haohao Du, 30 Mar 2021

Interactive discussion

Status: closed

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on os-2021-2', Anonymous Referee #1, 01 Mar 2021
    • AC1: 'Reply on RC1', Haohao Du, 06 Mar 2021
  • RC2: '关于 os-2021-2 的评论', Anonymous Referee #2, 29 Mar 2021
    • AC3: 'Reply on RC2', Haohao Du, 21 Apr 2021
  • RC3: 'Comment on os-2021-2', Anonymous Referee #2, 30 Mar 2021
    • AC2: 'Reply on RC3', Haohao Du, 30 Mar 2021
Gang Tang, Haohao Du, Xiong Hu, Yide Wang, Christophe Claramunt, and Shaoyang Men
Gang Tang, Haohao Du, Xiong Hu, Yide Wang, Christophe Claramunt, and Shaoyang Men

Viewed

Total article views: 1,309 (including HTML, PDF, and XML)
HTML PDF XML Total BibTeX EndNote
791 469 49 1,309 35 33
  • HTML: 791
  • PDF: 469
  • XML: 49
  • Total: 1,309
  • BibTeX: 35
  • EndNote: 33
Views and downloads (calculated since 28 Jan 2021)
Cumulative views and downloads (calculated since 28 Jan 2021)

Viewed (geographical distribution)

Total article views: 1,269 (including HTML, PDF, and XML) Thereof 1,268 with geography defined and 1 with unknown origin.
Country # Views %
  • 1
1
 
 
 
 

Cited

Latest update: 24 Apr 2024
Download

This preprint has been withdrawn.

Short summary
Accurate and significant wave height prediction with a couple of hours of warning time should offer major safety improvements for coastal and ocean engineering applications. However, significant wave height phenomenon is nonlinear and nonstationary, which makes any prediction simulation a non straightforward task. The aim of the research presented in this paper is to improve predicted significant wave height via a hybrid algorithm.