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OpenAlex Citation Counts

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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:

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

Showing 1-25 of 26 citing articles:

Robust Runoff Prediction With Explainable Artificial Intelligence and Meteorological Variables From Deep Learning Ensemble Model
Junhao Wu, Zhaocai Wang, Jinghan Dong, et al.
Water Resources Research (2023) Vol. 59, Iss. 9
Closed Access | Times Cited: 33
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
Significant wave height prediction based on variational mode decomposition and dual network model
Jiaxin Chen, Shibao Li, Jinze Zhu, et al.
Ocean Engineering (2025) Vol. 323, pp. 120533-120533
Closed Access | Times Cited: 1
Multivariate data decomposition based deep learning approach to forecast one-day ahead significant wave height for ocean energy generation
Zihao Zheng, Mumtaz Ali, Mehdi Jamei, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 185, pp. 113645-113645
Closed Access | Times Cited: 18
XWaveNet: Enabling uncertainty quantification in short-term ocean wave height forecasts and extreme event prediction
Soumyashree Kar, Jason McKenna, Vishwamithra Sunkara, et al.
Applied Ocean Research (2024) Vol. 148, pp. 103994-103994
Closed Access | Times Cited: 6
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
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
RIME-CNN-BiLSTM: A novel optimized hybrid enhanced model for significant wave height prediction in the Gulf of Mexico
Yining Wu, Jutao Wang, Runfeng Zhang, et al.
Ocean Engineering (2024) Vol. 312, pp. 119224-119224
Closed Access | Times Cited: 4
Decay regularized stochastic configuration networks with multi-level data processing for UAV Battery RUL Prediction
Zihao Liao, Shaobo Li, Peng Zhou, et al.
Information Sciences (2025) Vol. 701, pp. 121840-121840
Closed Access
A maintenance scheduling and non-full vessel routing strategy for offshore wind farms considering day-ahead environment interval forecasting
Guojin Si, Tangbin Xia, Kaigan Zhang, et al.
Ocean Engineering (2025) Vol. 321, pp. 120440-120440
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
A fast and accurate hybrid method for short-term forecasting significant wave height
Sheng Xu, Longfei Xiao, Huidong Zhang
Ocean Engineering (2024) Vol. 304, pp. 117914-117914
Closed Access | Times Cited: 3
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
Few-shot fault diagnosis for machinery using multi-scale perception multi-level feature fusion image quadrant entropy
Zhenya Wang, Liang Pan, Rengui Bai, et al.
Advanced Engineering Informatics (2024) Vol. 63, pp. 102972-102972
Closed Access | Times Cited: 3
A universal hydraulic-mechanical diagnostic framework based on feature extraction of abnormal on-field measurements: Application in micro pumped storage system
Zhigao Zhao, Fei Chen, Xianghui He, et al.
Applied Energy (2023) Vol. 357, pp. 122478-122478
Closed Access | Times Cited: 9
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
Prediction of significant wave height using a VMD-LSTM-rolling model in the South Sea of China
Tong Ding, De-an Wu, Liangshuai Shen, et al.
Frontiers in Marine Science (2024) Vol. 11
Open Access | Times Cited: 2
A generalized fault diagnosis framework for rotating machinery based on phase entropy
Zhenya Wang, Meng Zhang, Hui Chen, et al.
Reliability Engineering & System Safety (2024), pp. 110745-110745
Closed Access | Times Cited: 2
Wave Height Prediction in Maritime Transportation Using Decomposition Based Learning
T. Sharma, Jatin Bedi, Ashima Anand, et al.
IEEE Transactions on Intelligent Transportation Systems (2023) Vol. 25, Iss. 5, pp. 4304-4313
Closed Access | Times Cited: 4
Generalized machine learning models to predict significant wave height utilizing wind and atmospheric parameters
Abid Hasan, Imrul Kayes, Minhazul Alam, et al.
Energy Conversion and Management X (2024) Vol. 23, pp. 100623-100623
Open Access | Times Cited: 1
Hybrid intelligent models for predicting weekly mean significant wave heights
Dayong Han, Xinhua Xue
Ocean Engineering (2024) Vol. 310, pp. 118706-118706
Closed Access | Times Cited: 1
A Slow Failure Particle Swarm Optimization Long Short-Term Memory for Significant Wave Height Prediction
Jia Guo, Yan Zhou, Binghua Shi, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 8, pp. 1359-1359
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
A deep neural network with two-step decomposition technique for predicting ultra-short-term solar power and electrical load
Peter I. Udenze, Jiaqi Gong, S. Soltani, et al.
Applied Energy (2024) Vol. 382, pp. 125212-125212
Closed Access | Times Cited: 1
A novel hierarchical power allocation strategy considering severe wind power fluctuations for wind-storage integrated systems
Xidong Zheng, Feifei Bai, Zhiyuan Zhuang, et al.
International Journal of Electrical Power & Energy Systems (2023) Vol. 153, pp. 109363-109363
Open Access | Times Cited: 3
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