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Heave compensation prediction based on echo state network with correntropy induced loss function

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  • Xiaogang Huang
  • Dongge Lei
  • Lulu Cai
  • Tianhao Tang
  • Zhibin Wang

Abstract

In this paper, a new prediction approach is proposed for ocean vessel heave compensation based on echo state network (ESN). To improve the prediction accuracy and enhance the robustness against noise and outliers, a generalized similarity measure called correntropy is introduced into ESN training, which is referred as corr-ESN. An iterative method based on half-quadratic minimization is derived to train corr-ESN. The proposed corr-ESN is used for the heave motion prediction. The experimental results verify its effectiveness.

Suggested Citation

  • Xiaogang Huang & Dongge Lei & Lulu Cai & Tianhao Tang & Zhibin Wang, 2019. "Heave compensation prediction based on echo state network with correntropy induced loss function," PLOS ONE, Public Library of Science, vol. 14(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0217361
    DOI: 10.1371/journal.pone.0217361
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