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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.

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Showing 1-25 of 49 citing articles:

BiLSTM deep neural network model for imbalanced medical data of IoT systems
Marcin Woźniak, Michał Wieczorek, Jakub Siłka
Future Generation Computer Systems (2022) Vol. 141, pp. 489-499
Closed Access | Times Cited: 109
Near real-time wind speed forecast model with bidirectional LSTM networks
Lionel Joseph, Ravinesh C. Deo, Ramendra Prasad, et al.
Renewable Energy (2023) Vol. 204, pp. 39-58
Closed Access | Times Cited: 85
Deep learning for renewable energy forecasting: A taxonomy, and systematic literature review
Changtian Ying, Weiqing Wang, Jiong Yu, et al.
Journal of Cleaner Production (2022) Vol. 384, pp. 135414-135414
Closed Access | Times Cited: 76
Improving Significant Wave Height Forecasts Using a Joint Empirical Mode Decomposition–Long Short-Term Memory Network
Shuyi Zhou, Brandon J. Bethel, Wenjin Sun, et al.
Journal of Marine Science and Engineering (2021) Vol. 9, Iss. 7, pp. 744-744
Open Access | Times Cited: 63
New double decomposition deep learning methods for river water level forecasting
A. A. Masrur Ahmed, Ravinesh C. Deo, Afshin Ghahramani, et al.
The Science of The Total Environment (2022) Vol. 831, pp. 154722-154722
Closed Access | Times Cited: 48
An explainable multiscale LSTM model with wavelet transform and layer-wise relevance propagation for daily streamflow forecasting
Lizhi Tao, Zhichao Cui, Yufeng He, et al.
The Science of The Total Environment (2024) Vol. 929, pp. 172465-172465
Closed Access | Times Cited: 13
Assessment and prediction of significant wave height using hybrid CNN-BiLSTM deep learning model for sustainable wave energy in Australia
Nawin Raj, Reema Prakash
Sustainable Horizons (2024) Vol. 11, pp. 100098-100098
Open Access | Times Cited: 9
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
Prediction of significant wave height based on EEMD and deep learning
Tao Song, Jiarong Wang, Jidong Huo, et al.
Frontiers in Marine Science (2023) Vol. 10
Open Access | Times Cited: 22
Hybrid deep learning model for wave height prediction in Australia's wave energy region
A. A. Masrur Ahmed, S. Janifer Jabin Jui, Mohanad S. AL‐Musaylh, et al.
Applied Soft Computing (2023) Vol. 150, pp. 111003-111003
Open Access | Times Cited: 22
Forecasting hurricane-forced significant wave heights using a long short-term memory network in the Caribbean Sea
Brandon J. Bethel, Wenjin Sun, Changming Dong, et al.
Ocean science (2022) Vol. 18, Iss. 2, pp. 419-436
Open Access | Times Cited: 27
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
Exploring Wind Speed for Energy Considerations in Eastern Jerusalem-Palestine Using Machine-Learning Algorithms
Saeed Salah, Husain Alsamamra, Jawad H. Shoqeir
Energies (2022) Vol. 15, Iss. 7, pp. 2602-2602
Open Access | Times Cited: 24
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: 16
Assessment and Prediction of Sea Level and Coastal Wetland Changes in Small Islands Using Remote Sensing and Artificial Intelligence
Nawin Raj, Sarah Pasfield‐Neofitou
Remote Sensing (2024) Vol. 16, Iss. 3, pp. 551-551
Open Access | Times Cited: 6
Forecasting the Status of Municipal Waste in Smart Bins Using Deep Learning
Sabbir Ahmed, Sameera Mubarak, Jia Tina Du, et al.
International Journal of Environmental Research and Public Health (2022) Vol. 19, Iss. 24, pp. 16798-16798
Open Access | Times Cited: 21
Assessment and Prediction of Sea Level Trend in the South Pacific Region
Nawin Raj, Zahra Gharineiat, A. A. Masrur Ahmed, et al.
Remote Sensing (2022) Vol. 14, Iss. 4, pp. 986-986
Open Access | Times Cited: 20
A coupled CEEMD-BiLSTM model for regional monthly temperature prediction
Xianqi Zhang, Yimeng Xiao, Guoyu Zhu, et al.
Environmental Monitoring and Assessment (2023) Vol. 195, Iss. 3
Closed Access | Times Cited: 12
A Bidirectional Long Short-Term Memory Model Algorithm for Predicting COVID-19 in Gulf Countries
Theyazn H. H. Aldhyani, Hasan Alkahtani
Life (2021) Vol. 11, Iss. 11, pp. 1118-1118
Open Access | Times Cited: 27
Estimation of Coastal Wetland Soil Organic Carbon Content in Western Bohai Bay Using Remote Sensing, Climate, and Topographic Data
Yongbin Zhang, Caiyao Kou, Mingyue Liu, et al.
Remote Sensing (2023) Vol. 15, Iss. 17, pp. 4241-4241
Open Access | Times Cited: 10
A novel multivariable hybrid model to improve short and long-term significant wave height prediction
Junheng Pang, Sheng Dong
Applied Energy (2023) Vol. 351, pp. 121813-121813
Closed Access | Times Cited: 10
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
Short-term significant wave height prediction using adaptive variational mode decomposition and error-compensation model
Junheng Pang, Sheng Dong
Applied Ocean Research (2025) Vol. 158, pp. 104519-104519
Open Access
A hybrid model for significant wave height prediction based on an improved empirical wavelet transform decomposition and long-short term memory network
Jin Wang, Brandon J. Bethel, Wenhong Xie, et al.
Ocean Modelling (2024) Vol. 189, pp. 102367-102367
Closed Access | Times Cited: 3
A two-module bias-correction model for sea wave hindcasting based on the long-short term memory neural network
Jiawen Liao, Yineng Li, Junmin Li, et al.
Ocean Engineering (2024) Vol. 311, pp. 118827-118827
Closed Access | Times Cited: 3
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