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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:

Short-term multi-step wind power forecasting based on spatio-temporal correlations and transformer neural networks
Shilin Sun, Yuekai Liu, Qi Li, et al.
Energy Conversion and Management (2023) Vol. 283, pp. 116916-116916
Closed Access | Times Cited: 99

Showing 1-25 of 99 citing articles:

Renewable energy as an alternative source for energy management in agriculture
Yaqoob Majeed, Muhammad Usman Khan, Muhammad Waseem, et al.
Energy Reports (2023) Vol. 10, pp. 344-359
Open Access | Times Cited: 139
Optimization of a hybrid solar/wind/storage system with bio-generator for a household by emerging metaheuristic optimization algorithm
Jingya Fan, Xiao Zhou
Journal of Energy Storage (2023) Vol. 73, pp. 108967-108967
Closed Access | Times Cited: 65
A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods
Chu Zhang, Yuhan Wang, Yongyan Fu, et al.
Energy Conversion and Management (2024) Vol. 301, pp. 118045-118045
Closed Access | Times Cited: 23
Optimizing multi-step wind power forecasting: Integrating advanced deep neural networks with stacking-based probabilistic learning
Lucas de Azevedo Takara, Ana Clara Teixeira, Hamed Yazdanpanah, et al.
Applied Energy (2024) Vol. 369, pp. 123487-123487
Closed Access | Times Cited: 23
Regional wind-photovoltaic combined power generation forecasting based on a novel multi-task learning framework and TPA-LSTM
Yuejiang Chen, Jiang‐Wen Xiao, Yan‐Wu Wang, et al.
Energy Conversion and Management (2023) Vol. 297, pp. 117715-117715
Closed Access | Times Cited: 28
Digital twin of wind farms via physics-informed deep learning
Jincheng Zhang, Xiaowei Zhao
Energy Conversion and Management (2023) Vol. 293, pp. 117507-117507
Open Access | Times Cited: 26
Attention mechanism is useful in spatio-temporal wind speed prediction: Evidence from China
Chengqing Yu, Guangxi Yan, Chengming Yu, et al.
Applied Soft Computing (2023) Vol. 148, pp. 110864-110864
Closed Access | Times Cited: 25
A location-centric transformer framework for multi-location short-term wind speed forecasting
Luyang Zhao, Changliang Liu, Chaojie Yang, et al.
Energy Conversion and Management (2025) Vol. 328, pp. 119627-119627
Closed Access | Times Cited: 1
Quantile-transformed multi-attention residual framework (QT-MARF) for medium-term PV and wind power prediction
Adeel Feroz Mirza, Zhaokun Shu, Muhammad Usman, et al.
Renewable Energy (2023) Vol. 220, pp. 119604-119604
Closed Access | Times Cited: 21
Economic operation of networked flexi-renewable energy hubs with thermal and hydrogen storage systems based on the market clearing price model
Mohammad-Reza Akbari-Zadeh, Taher Niknam, Hossein Jokar
International Journal of Hydrogen Energy (2023) Vol. 50, pp. 1-18
Closed Access | Times Cited: 19
Temporal collaborative attention for wind power forecasting
Yue Hu, Hanjing Liu, Senzhen Wu, et al.
Applied Energy (2023) Vol. 357, pp. 122502-122502
Open Access | Times Cited: 17
STELLM: Spatio-temporal enhanced pre-trained large language model for wind speed forecasting
Tangjie Wu, Qiang Ling
Applied Energy (2024) Vol. 375, pp. 124034-124034
Closed Access | Times Cited: 8
Green energy forecasting using multiheaded convolutional LSTM model for sustainable life
Peng Liu, Quan Feng, Yuxuan Gao, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 63, pp. 103609-103609
Closed Access | Times Cited: 7
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
The motion forecasting study of floating offshore wind turbine using self-attention long short-term memory method
Sijia Deng, Dezhi Ning, Robert Mayon
Ocean Engineering (2024) Vol. 310, pp. 118709-118709
Closed Access | Times Cited: 7
A novel ultra-short-term wind power forecasting method based on TCN and Informer models
Qi Li, Xiaoying Ren, Fei Zhang, et al.
Computers & Electrical Engineering (2024) Vol. 120, pp. 109632-109632
Closed Access | Times Cited: 6
DTTM: A deep temporal transfer model for ultra-short-term online wind power forecasting
Mingwei Zhong, Cancheng Xu, Zikang Xian, et al.
Energy (2023) Vol. 286, pp. 129588-129588
Closed Access | Times Cited: 14
A privacy-preserving framework integrating federated learning and transfer learning for wind power forecasting
Yugui Tang, Shujing Zhang, Zhen Zhang
Energy (2023) Vol. 286, pp. 129639-129639
Closed Access | Times Cited: 14
An enhanced feature extraction based long short-term memory neural network for wind power forecasting via considering the missing data reconstruction
Zheng Xin, Xingran Liu, Hanyuan Zhang, et al.
Energy Reports (2023) Vol. 11, pp. 97-114
Open Access | Times Cited: 14
Interpretable Wind Power Short-Term Power Prediction Model Using Deep Graph Attention Network
Jinhua Zhang, Hui Li, Peng Cheng, et al.
Energies (2024) Vol. 17, Iss. 2, pp. 384-384
Open Access | Times Cited: 5
A new decomposition-ensemble strategy fusion with correntropy optimization learning algorithms for short-term wind speed prediction
Ning Zhao, Yi Su, Xianxing Dai, et al.
Applied Energy (2024) Vol. 369, pp. 123589-123589
Closed Access | Times Cited: 5
Short-term wind power forecasting based on multi-scale receptive field-mixer and conditional mixture copula
Jinchang Li, Jiapeng Chen, Z. Q. Chen, et al.
Applied Soft Computing (2024) Vol. 164, pp. 112007-112007
Closed Access | Times Cited: 5
Using enhanced Variational Modal Decomposition and Dung Beetle Optimization Algorithm optimization-kernel Extreme Learning Machine model to forecast short-term wind power
Guodong You, Z. Chang, Xing-Yun Li, et al.
Electric Power Systems Research (2024) Vol. 236, pp. 110904-110904
Closed Access | Times Cited: 5
Wind power prediction through acoustic data-driven online modeling and active wake control
Bingchuan Sun, Mingxu Su, Jié He
Energy Conversion and Management (2024) Vol. 319, pp. 118920-118920
Closed Access | Times Cited: 5
Non-crossing quantile probabilistic forecasting of cluster wind power considering spatio-temporal correlation
Yuejiang Chen, Jiang‐Wen Xiao, Yan‐Wu Wang, et al.
Applied Energy (2024) Vol. 377, pp. 124356-124356
Closed Access | Times Cited: 5
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