Heave compensation prediction based on echo state network with correntropy induced loss function.
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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.
SUBMITTER: Huang X
PROVIDER: S-EPMC6563959 | biostudies-literature |
REPOSITORIES: biostudies-literature
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