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

被引：4

作者：

Huang, Xiaogang ^{[1
,2
]}

Lei, Dongge ^{[2
]}

Cai, Lulu ^{[2
]}

Tang, Tianhao ^{[1
]}

Wang, Zhibin ^{[3
]}

机构：

[1] Shanghai Maritime Univ, Coll Logist Engn, Dept Elect Automat, Shanghai, Peoples R China

[2] Quzhou Univ, Coll Elect & Informat Engn, Quzhou, Peoples R China

[3] Yanshan Univ, Inst Elect Engn, Qinhuangdao, Hebei, Peoples R China

来源：

PLOS ONE | 2019年 / 14卷 / 06期

关键词：

D O I：

10.1371/journal.pone.0217361

中图分类号：

O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];

学科分类号：

07 ; 0710 ; 09 ;

摘要：

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.

引用

页数：10

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