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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:

The data-based adaptive graph learning network for analysis and prediction of offshore wind speed
Yuting Ren, Zhuolin Li, Lingyu Xu, et al.
Energy (2023) Vol. 267, pp. 126590-126590
Closed Access | Times Cited: 22

Showing 22 citing articles:

A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information
Mao Yang, Chao Han, Wei Zhang, et al.
Energy (2024) Vol. 294, pp. 130770-130770
Closed Access | Times Cited: 17
Integrating sentiment analysis with graph neural networks for enhanced stock prediction: A comprehensive survey
Nabanita Das, Bikash Sadhukhan, Rajdeep Chatterjee, et al.
Decision Analytics Journal (2024) Vol. 10, pp. 100417-100417
Open Access | Times Cited: 13
Dynamic adaptive spatio-temporal graph neural network for multi-node offshore wind speed forecasting
Ziheng Gao, Zhuolin Li, Lingyu Xu, et al.
Applied Soft Computing (2023) Vol. 141, pp. 110294-110294
Closed Access | Times Cited: 18
Carbon emission causal discovery and multi-step forecasting for global cities
Xuedong Liang, Xiaoyan Li
Cities (2024) Vol. 148, pp. 104881-104881
Closed Access | Times Cited: 8
BERT4ST:: Fine-tuning pre-trained large language model for wind power forecasting
Zefeng Lai, Tangjie Wu, Xihong Fei, et al.
Energy Conversion and Management (2024) Vol. 307, pp. 118331-118331
Closed Access | Times Cited: 7
Carbon emission causal discovery and multi-step forecasting using spatiotemporal information
Xiaoyan Li, Wenting Zhan, Peng Luo, et al.
Information Sciences (2024) Vol. 665, pp. 120372-120372
Closed Access | Times Cited: 5
Unveiling causal dynamics and forecasting of urban carbon emissions in major emitting economies through multisource interaction
Xuedong Liang, Wenting Zhan, Xiaoyan Li, et al.
Sustainable Cities and Society (2024) Vol. 105, pp. 105326-105326
Closed Access | Times Cited: 5
Graph neural network-based lithium-ion battery state of health estimation using partial discharging curve
Kate Qi Zhou, Yan Qin, Chau Yuen
Journal of Energy Storage (2024) Vol. 100, pp. 113502-113502
Open Access | Times Cited: 5
An Interpretable Deep Inference Model With Dynamic Constraints for Forecasting the Evolution of Sea Surface Variables in the South China Sea
Qi Shao, G. C. Hou, Wei Li, et al.
Geophysical Research Letters (2025) Vol. 52, Iss. 2
Open Access
Multi-scale spatiotemporal wind forecasting network in Southwest China
Xiao Yang, Fei Luo, Siyu Chen
Earth Science Informatics (2025) Vol. 18, Iss. 2
Closed Access
Short-term offshore wind speed forecasting approach based on multi-stage decomposition and deep residual network with self-attention
Hakan Açıkgöz, Deniz Korkmaz
Engineering Applications of Artificial Intelligence (2025) Vol. 146, pp. 110313-110313
Closed Access
Self-supervised dynamic stochastic graph network for spatio-temporal wind speed forecasting
Tangjie Wu, Qiang Ling
Energy (2024) Vol. 304, pp. 132056-132056
Closed Access | Times Cited: 3
Deep learning for spatiotemporal forecasting in Earth system science: a review
Manzhu Yu, Qunying Huang, Zhenlong Li
International Journal of Digital Earth (2024) Vol. 17, Iss. 1
Open Access | Times Cited: 3
Change Detection for Forest Ecosystems Using Remote Sensing Images with Siamese Attention U-Net
Ashen Iranga Hewarathna, Luke Hamlin, J. B. Charles, et al.
Technologies (2024) Vol. 12, Iss. 9, pp. 160-160
Open Access | Times Cited: 3
Graph neural network incorporating time-varying frequency domain features with application in spatial wind speed field prediction
Chuanjin Yu, Yongle Li
Journal of Wind Engineering and Industrial Aerodynamics (2024) Vol. 253, pp. 105875-105875
Closed Access | Times Cited: 2
Spatiotemporal Deep-Learning Model With Graph Convolutional Network for Well Logs Prediction
Feng Shuo, Xuegui Li, Fang Zeng, et al.
IEEE Geoscience and Remote Sensing Letters (2023) Vol. 20, pp. 1-5
Closed Access | Times Cited: 4
A dual spatio-temporal network for short-term wind power forecasting
Zefeng Lai, Qiang Ling
Sustainable Energy Technologies and Assessments (2023) Vol. 60, pp. 103486-103486
Closed Access | Times Cited: 4
Short-Term Marine Wind Speed Forecasting Based on Dynamic Graph Embedding and Spatiotemporal Information
Dibo Dong, Shangwei Wang, Qiaoying Guo, et al.
Journal of Marine Science and Engineering (2024) Vol. 12, Iss. 3, pp. 502-502
Open Access | Times Cited: 1
Multi-step prediction of offshore wind power based on Transformer network and Huber loss
Haoyi Xiao, Xiaoxia He, Chunli Li
International Journal of Electrical Power & Energy Systems (2024) Vol. 162, pp. 110229-110229
Open Access | Times Cited: 1
EEMD-ConvLSTM: a model for short-term prediction of two-dimensional wind speed in the South China Sea
Handan Sun, Tao Song, Ying Li, et al.
Applied Intelligence (2023) Vol. 53, Iss. 24, pp. 30186-30202
Closed Access | Times Cited: 2
Multi-Step Prediction of Offshore Wind Power Based on Transformer Network and Huber Loss
Xiaoxia He, Haoyi Xiao, Chunli Li
(2024)
Closed Access
A significant wave height prediction method with ocean characteristics fusion and spatiotemporal dynamic graph modeling
Yin Xiao, Taoxing Wu, Jie Yu, et al.
Acta Oceanologica Sinica (2024) Vol. 43, Iss. 12, pp. 13-33
Closed Access
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