A data-driven approach for predicting depth-averaged velocities in the early stages of underwater glider navigation-Reference-Cited by-同舟云学术

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A data-driven approach for predicting depth-averaged velocities in the early stages of underwater glider navigation

Published:2024-05 Issue: Volume:299 Page:117417
ISSN:0029-8018
Container-title:Ocean Engineering
language:en
Short-container-title:Ocean Engineering

Author:

Li Hualing,Zhou Yaojian,Zhao Yuning,Wang Meishu,Wang Zijian

Funder

National Natural Science Foundation of China

Shanxi Province Natural Science Foundation

Liaoning Provincial Natural Science Foundation

Publisher

Elsevier BV

Reference20 articles.

1. XGBoost: A Scalable Tree Boosting System;Chen,2016

2. Finding structure in time;Elman;Cogn. Sci.,1990

3. Seaglider: a long-range autonomous underwater vehicle for oceanographic research;Eriksen;IEEE J. Ocean. Eng.,2001

4. Data-driven depth-averaged current prediction methods for underwater gliders with sailing parameters;Feng;AIP Adv.,2023

5. Long short-term memory;Hochreiter;Neural Comput.,1997

Cited by 1 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Modelling and analysis of depth-averaged currents for underwater gliders;Ocean Engineering;2024-11

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