Journal
PLOS ONE
Volume 14, Issue 6, Pages -Publisher
PUBLIC LIBRARY SCIENCE
DOI: 10.1371/journal.pone.0217361
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Funding
- Zhejiang Province Public Welfare Project [LGG19F050003]
- Project of Shanghai Maritime University Graduate Student Innovation [2015YCX073]
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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.
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