Open Access Helper

OpenAlex Citation Counts

OpenAlex Citations Logo

OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Wave height forecast method with multi-step training set extension LSTM neural network
Ji Yao, Wenhua Wu
Ocean Engineering (2022) Vol. 263, pp. 112432-112432
Closed Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

A hybrid VMD-LSTM/GRU model to predict non-stationary and irregular waves on the east coast of China
Lingxiao Zhao, Zhiyang Li, Leilei Qu, et al.
Ocean Engineering (2023) Vol. 276, pp. 114136-114136
Closed Access | Times Cited: 86
Wave energy forecasting: A state-of-the-art survey and a comprehensive evaluation
Ruobin Gao, Xiaocai Zhang, Maohan Liang, et al.
Applied Soft Computing (2025) Vol. 170, pp. 112652-112652
Closed Access | Times Cited: 1
Point and interval prediction for significant wave height based on LSTM-GRU and KDE
Mie Wang, Feixiang Ying
Ocean Engineering (2023) Vol. 289, pp. 116247-116247
Closed Access | Times Cited: 20
An integrated decomposition algorithm based bidirectional LSTM neural network approach for predicting ocean wave height and ocean wave energy
Karan Sareen, Bijaya Ketan Panigrahi, Tushar Shikhola, et al.
Ocean Engineering (2023) Vol. 281, pp. 114852-114852
Closed Access | Times Cited: 17
Bio-multisensory-inspired gate-attention coordination model for forecasting short-term significant wave height
Han Wu, Xiao‐Zhi Gao, Jiani Heng
Energy (2024) Vol. 294, pp. 130887-130887
Closed Access | Times Cited: 7
Multi-step-ahead significant wave height prediction using a hybrid model based on an innovative two-layer decomposition framework and LSTM
Fu Yang, Feixiang Ying, Lingling Huang, et al.
Renewable Energy (2022) Vol. 203, pp. 455-472
Closed Access | Times Cited: 26
An Integrated Complete Ensemble Empirical Mode Decomposition with Adaptive Noise to Optimize LSTM for Significant Wave Height Forecasting
Lingxiao Zhao, Zhiyang Li, Junsheng Zhang, et al.
Journal of Marine Science and Engineering (2023) Vol. 11, Iss. 2, pp. 435-435
Open Access | Times Cited: 15
Human-cognition-inspired deep model with its application to ocean wave height forecasting
Han Wu, Yan Liang, Xiao‐Zhi Gao, et al.
Expert Systems with Applications (2023) Vol. 230, pp. 120606-120606
Closed Access | Times Cited: 13
Long time series of ocean wave prediction based on PatchTST model
Xinyu Huang, Jun Tang, Yongming Shen
Ocean Engineering (2024) Vol. 301, pp. 117572-117572
Closed Access | Times Cited: 5
ANN-LSTM-A Water Consumption Prediction Based on Attention Mechanism Enhancement
Xin Zhou, Xin Meng, Zhenyu Li
Energies (2024) Vol. 17, Iss. 5, pp. 1102-1102
Open Access | Times Cited: 4
Single-instant spatial wave height forecast using machine learning: An image-to-image translation approach based on generative adversarial networks
Zilong Ti, Yunfei Kong
Applied Ocean Research (2024) Vol. 150, pp. 104094-104094
Closed Access | Times Cited: 4
An innovative deep learning model for accurate wave height predictions with enhanced performance for extreme waves
Xinlin Lü, Zhong Peng, C. Li, et al.
Ocean Engineering (2025) Vol. 322, pp. 120502-120502
Closed Access
Ensemble learning based approach for the prediction of monthly significant wave heights
Jinzhou Chen, Xinhua Xue
Renewable Energy (2025), pp. 122732-122732
Closed Access
Significant Wave Height Prediction Based on Improved Fuzzy C-Means Clustering and Bivariate Kernel Density Estimation
Jianguo Zhou, Luming Zhou, Yunlong Zhao, et al.
Renewable Energy (2025), pp. 122787-122787
Closed Access
Left-right brain interaction inspired bionic deep network for forecasting significant wave height
Han Wu, Yan Liang, Xiao‐Zhi Gao
Energy (2023) Vol. 278, pp. 127995-127995
Closed Access | Times Cited: 10
Solving the temporal lags in local significant wave height prediction with a new VMD-LSTM model
Shaotong Zhang, Zixi Zhao, Jinran Wu, et al.
Ocean Engineering (2024) Vol. 313, pp. 119385-119385
Closed Access | Times Cited: 3
An integrated system to significant wave height prediction: Combining feature engineering, multi-criteria decision making, and hybrid kernel density estimation
Kang Wang, Yanru Liu, Qianyi Xing, et al.
Expert Systems with Applications (2023) Vol. 241, pp. 122351-122351
Closed Access | Times Cited: 7
STGWN: Enhanced spatiotemporal wave forecasting using multiscale features
Aming Yue, Wenhua Wu
Applied Ocean Research (2024) Vol. 145, pp. 103923-103923
Closed Access | Times Cited: 2
Real-time prediction of full-scale ship maneuvering motions at sea under random rudder actions based on BiLSTM-SAT hybrid method
Xiaofang Zhou, Lu Zou, Hongwei He, et al.
Ocean Engineering (2024) Vol. 314, pp. 119664-119664
Closed Access | Times Cited: 2
Tidal analysis and prediction based on the Fourier basis pursuit spectrum
Feng Gao, Guocheng Wang, Lintao Liu, et al.
Ocean Engineering (2023) Vol. 278, pp. 114414-114414
Open Access | Times Cited: 4
Disentangled Seasonal-Trend representation of improved CEEMD-GRU joint model with entropy-driven reconstruction to forecast significant wave height
Lingxiao Zhao, Zhiyang Li, Yuguo Pei, et al.
Renewable Energy (2024) Vol. 226, pp. 120345-120345
Closed Access | Times Cited: 1
Predicting ship responses in different seaways using a generalizable force correcting machine learning method
Kyle E. Marlantes, Piotr J. Bandyk, Kevin J. Maki
Ocean Engineering (2024) Vol. 312, pp. 119110-119110
Open Access | Times Cited: 1
Multiple-step accurate prediction of wave energy: A hybrid model based on quadratic decomposition, SSA and LSTM
Jianhui Wang, Dong Zhang, Qin Huang, et al.
International Journal of Green Energy (2024), pp. 1-24
Closed Access | Times Cited: 1
Wave height forecast method with uncertainty quantification based on Gaussian process regression
Zi-Lu Ouyang, C. H. Li, Ke Zhan, et al.
Journal of Hydrodynamics (2024)
Closed Access | Times Cited: 1
Long Time Series of Ocean Wave Prediction Based on Patchtst Model
Xinyu Huang, Jun Tang, Yongming Shen
(2023)
Closed Access | Times Cited: 3
Page 1 - Next Page

Scroll to top