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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:

Combined Approach for Short-Term Wind Power Forecasting Based on Wave Division and Seq2Seq Model Using Deep Learning
Lin Ye, Binhua Dai, Ming Pei, et al.
IEEE Transactions on Industry Applications (2022) Vol. 58, Iss. 2, pp. 2586-2596
Closed Access | Times Cited: 49

Showing 1-25 of 49 citing articles:

A wavelet-LSTM model for short-term wind power forecasting using wind farm SCADA data
Zhaohua Liu, Chang-Tong Wang, Hua‐Liang Wei, et al.
Expert Systems with Applications (2024) Vol. 247, pp. 123237-123237
Closed Access | Times Cited: 18
Hybrid model for short-term wind power forecasting based on singular spectrum analysis and a temporal convolutional attention network with an adaptive receptive field
Zhen Shao, Jun Han, Wei Zhao, et al.
Energy Conversion and Management (2022) Vol. 269, pp. 116138-116138
Closed Access | Times Cited: 38
A Review of Modern Wind Power Generation Forecasting Technologies
Wen-Chang Tsai, Chih-Ming Hong, Chia‐Sheng Tu, et al.
Sustainability (2023) Vol. 15, Iss. 14, pp. 10757-10757
Open Access | Times Cited: 23
Dynamic Temporal Dependency Model for Multiple Steps Ahead Short-Term Load Forecasting of Power System
Bozhen Jiang, Hongyuan Yang, Yidi Wang, et al.
IEEE Transactions on Industry Applications (2024) Vol. 60, Iss. 4, pp. 5244-5254
Closed Access | Times Cited: 12
Short-Term Wind Power Prediction Based on Multi-Parameters Similarity Wind Process Matching and Weighed-Voting-Based Deep Learning Model Selection
Zimin Yang, Xiaosheng Peng, Jiajiong Song, et al.
IEEE Transactions on Power Systems (2023) Vol. 39, Iss. 1, pp. 2129-2142
Closed Access | Times Cited: 18
Short-Term Wind Power Forecast Based on Continuous Conditional Random Field
Menglin Li, Ming Yang, Yixiao Yu, et al.
IEEE Transactions on Power Systems (2023) Vol. 39, Iss. 1, pp. 2185-2197
Closed Access | Times Cited: 17
Deterministic and Probabilistic Wind Power Forecasts by Considering Various Atmospheric Models and Feature Engineering Approaches
Yuan‐Kang Wu, Cheng‐Liang Huang, Sheng-Hong Wu, et al.
IEEE Transactions on Industry Applications (2022) Vol. 59, Iss. 1, pp. 192-206
Closed Access | Times Cited: 25
Spatio-Temporal Graph Neural Network and Pattern Prediction Based Ultra-Short-Term Power Forecasting of Wind Farm Cluster
Xiaoyan Liu, Yiran Zhang, Zhao Zhen, et al.
IEEE Transactions on Industry Applications (2023) Vol. 60, Iss. 1, pp. 1794-1803
Closed Access | Times Cited: 14
A Review of Modern Wind Power Generation Forecasting Technologies
Wen-Chang Tsai, Chih-Ming Hong, Whei-Min Lin, et al.
(2023)
Open Access | Times Cited: 13
MISMS: a multistep-ahead and interpretable sequential modelling scheme for the long-term dynamic forecasting in process industries
Wenshuo Song, Weihua Cao, Yan Yuan, et al.
International Journal of Systems Science (2025), pp. 1-18
Closed Access
A Lightweight Framework for Rapid Response to Short-Term Forecasting of Wind Farms Using Dual Scale Modeling and Normalized Feature Learning
Yan Chen, Miaolin Yu, Haochong Wei, et al.
Energies (2025) Vol. 18, Iss. 3, pp. 580-580
Open Access
Multi-step ahead wind power forecasting based on multi-feature wavelet decomposition and convolution-gated recurrent unit model
S.N. Shringi, Lalit Mohan Saini, S. K. Aggarwal
Electrical Engineering (2025)
Closed Access
Research on Wind Power Short-Term Forecasting Method Based on Temporal Convolutional Neural Network and Variational Modal Decomposition
Jing-Wei Tang, Ying‐Ren Chien
Sensors (2022) Vol. 22, Iss. 19, pp. 7414-7414
Open Access | Times Cited: 21
A Hybrid Model for Long-Term Wind Power Forecasting Utilizing NWP Subsequence Correction and Multi-Scale Deep Learning Regression Methods
Yu Chang, Yang Han, Yuxi Chen, et al.
IEEE Transactions on Sustainable Energy (2023) Vol. 15, Iss. 1, pp. 263-275
Closed Access | Times Cited: 11
An Interval Prediction Approach of Wind Power Based on Skip-GRU and Block-Bootstrap Techniques
Hao Quan, Wei Zhang, Wenjie Zhang, et al.
IEEE Transactions on Industry Applications (2023), pp. 1-10
Closed Access | Times Cited: 10
A Novel Coupled Optimization Prediction Model for Air Quality
Q. Shao, Jiahao Chen, Tao Jiang
IEEE Access (2023) Vol. 11, pp. 69667-69685
Open Access | Times Cited: 9
Hybrid dynamic modeling of an industrial reactor network with first-principles and data-driven approaches
Changrui Xie, Runjie Yao, Lingyu Zhu, et al.
Chemical Engineering Science (2024) Vol. 289, pp. 119852-119852
Closed Access | Times Cited: 3
Two-stage correction prediction of wind power based on numerical weather prediction wind speed superposition correction and improved clustering
Mao Yang, Yunfeng Guo, Fulin Fan, et al.
Energy (2024) Vol. 302, pp. 131797-131797
Closed Access | Times Cited: 3
Short-Term Wind Power Forecasting Based on Feature Analysis and Error Correction
Zifa Liu, Xinyi Li, Haiyan Zhao
Energies (2023) Vol. 16, Iss. 10, pp. 4249-4249
Open Access | Times Cited: 8
Short-Term Forecasting of Wind Power Based on Error Traceability and Numerical Weather Prediction Wind Speed Correction
Mao Yang, Yue Wen Jiang, Jianfeng Che, et al.
Electronics (2024) Vol. 13, Iss. 8, pp. 1559-1559
Open Access | Times Cited: 2
A Novel Hybrid Ensemble Learning Approach for Enhancing Accuracy and Sustainability in Wind Power Forecasting
Farhan Ullah, Xuexia Zhang, Mansoor Khan, et al.
Computers, materials & continua/Computers, materials & continua (Print) (2024) Vol. 79, Iss. 2, pp. 3373-3395
Open Access | Times Cited: 2
Short‐Term Offshore Wind Power Prediction Based on Significant Weather Process Classification and Multitask Learning Considering Neighboring Powers
Zimin Yang, Xiaosheng Peng, Xiaobin Zhang, et al.
Wind Energy (2024) Vol. 27, Iss. 10, pp. 1011-1023
Open Access | Times Cited: 2
Probabilistic online learning framework for short-term wind power forecasting using ensemble bagging regression model
Arun K. Nayak, Kailash Chand Sharma, Rohit Bhakar, et al.
Energy Conversion and Management (2024) Vol. 323, pp. 119142-119142
Closed Access | Times Cited: 2
A novel ultra-short-term wind power prediction method based on XA mechanism
Cheng Peng, Yiqin Zhang, Bowen Zhang, et al.
Applied Energy (2023) Vol. 351, pp. 121905-121905
Closed Access | Times Cited: 5
Significant wave height forecasts integrating ensemble empirical mode decomposition with sequence-to-sequence model
Lina Wang, Yu Cao, Xilin Deng, et al.
Acta Oceanologica Sinica (2023) Vol. 42, Iss. 10, pp. 54-66
Closed Access | Times Cited: 5
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