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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:

A combination forecasting model of wind speed based on decomposition
Zhongda Tian, Hao Li, Feihong Li
Energy Reports (2021) Vol. 7, pp. 1217-1233
Open Access | Times Cited: 78

Showing 1-25 of 78 citing articles:

Short-term multi-hour ahead country-wide wind power prediction for Germany using gated recurrent unit deep learning
Farah Shahid, Wood David A., Nisar Humaira, et al.
Renewable and Sustainable Energy Reviews (2022) Vol. 167, pp. 112700-112700
Closed Access | Times Cited: 84
Short-term wind power prediction method based on CEEMDAN-GWO-Bi-LSTM
Hongbin Sun, Qing Cui, Jingya Wen, et al.
Energy Reports (2024) Vol. 11, pp. 1487-1502
Open Access | Times Cited: 16
Evaluating the Accuracy of the ERA5 Model in Predicting Wind Speeds Across Coastal and Offshore Regions
Mohamad Alkhalidi, Abdullah N. Al–Dabbous, Shoug Kh. Al-Dabbous, et al.
Journal of Marine Science and Engineering (2025) Vol. 13, Iss. 1, pp. 149-149
Open Access | Times Cited: 2
A novel decomposition-ensemble prediction model for ultra-short-term wind speed
Zhongda Tian, Hao Chen
Energy Conversion and Management (2021) Vol. 248, pp. 114775-114775
Closed Access | Times Cited: 101
Artificial Neural Networks Hidden Unit and Weight Connection Optimization by Quasi-Refection-Based Learning Artificial Bee Colony Algorithm
Nebojša Bačanin, Timea Bezdan, K. Venkatachalam, et al.
IEEE Access (2021) Vol. 9, pp. 169135-169155
Open Access | Times Cited: 72
A simple approach for short-term wind speed interval prediction based on independently recurrent neural networks and error probability distribution
Adnan Saeed, Chaoshun Li, Zhenhao Gan, et al.
Energy (2021) Vol. 238, pp. 122012-122012
Closed Access | Times Cited: 62
Energy forecasting model based on CNN-LSTM-AE for many time series with unequal lengths
Rodney Rick, Lilian Berton
Engineering Applications of Artificial Intelligence (2022) Vol. 113, pp. 104998-104998
Closed Access | Times Cited: 55
Wind speed prediction using measurements from neighboring locations and combining the extreme learning machine and the AdaBoost algorithm
Lili Wang, Yan Guo, Manhong Fan, et al.
Energy Reports (2022) Vol. 8, pp. 1508-1518
Open Access | Times Cited: 43
A novel approach to ultra-short-term wind power prediction based on feature engineering and informer
Wei Hui, Wensheng Wang, Xiaoxuan Kao
Energy Reports (2022) Vol. 9, pp. 1236-1250
Open Access | Times Cited: 43
A new hybrid optimization prediction model for PM2.5 concentration considering other air pollutants and meteorological conditions
Hong Yang, Zehang Liu, Guohui Li
Chemosphere (2022) Vol. 307, pp. 135798-135798
Closed Access | Times Cited: 42
A combined model for short-term wind power forecasting based on the analysis of numerical weather prediction data
Boyu He, Lin Ye, Ming Pei, et al.
Energy Reports (2021) Vol. 8, pp. 929-939
Open Access | Times Cited: 52
Data-Adaptive Censoring for Short-Term Wind Speed Predictors Based on MLP, RNN, and SVM
A.O. Sarp, Engin Cemal Mengüç, Murat Peker, et al.
IEEE Systems Journal (2022) Vol. 16, Iss. 3, pp. 3625-3634
Closed Access | Times Cited: 37
Short-term Wind Power Forecasting Using the Hybrid Model of Improved Variational Mode Decomposition and Maximum Mixture Correntropy Long Short-term Memory Neural Network
Wenchao Lu, Jiandong Duan, Peng Wang, et al.
International Journal of Electrical Power & Energy Systems (2022) Vol. 144, pp. 108552-108552
Closed Access | Times Cited: 33
An ultra‐short‐term wind speed prediction model using LSTM based on modified tuna swarm optimization and successive variational mode decomposition
Wumaier Tuerxun, Chang Xu, Hongyu Guo, et al.
Energy Science & Engineering (2022) Vol. 10, Iss. 8, pp. 3001-3022
Open Access | Times Cited: 30
Decomposition-based wind power forecasting models and their boundary issue: An in-depth review and comprehensive discussion on potential solutions
Yinsong Chen, Samson S. Yu, Shama Naz Islam, et al.
Energy Reports (2022) Vol. 8, pp. 8805-8820
Open Access | Times Cited: 30
Serial-parallel dynamic echo state network: A hybrid dynamic model based on a chaotic coyote optimization algorithm for wind speed prediction
Lin Ding, Yulong Bai, Manhong Fan, et al.
Expert Systems with Applications (2022) Vol. 212, pp. 118789-118789
Closed Access | Times Cited: 30
Harmony search: Current studies and uses on healthcare systems
Maryam T. Abdulkhaleq, Tarik A. Rashid, Abeer Alsadoon, et al.
Artificial Intelligence in Medicine (2022) Vol. 131, pp. 102348-102348
Open Access | Times Cited: 29
Wind speed prediction in China with fully-convolutional deep neural network
Zongwei Zhang, Lianlei Lin, Sheng Gao, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 201, pp. 114623-114623
Closed Access | Times Cited: 7
WSFNet: An efficient wind speed forecasting model using channel attention-based densely connected convolutional neural network
Hakan Açıkgöz, Ümit Budak, Deniz Korkmaz, et al.
Energy (2021) Vol. 233, pp. 121121-121121
Closed Access | Times Cited: 35
A novel hybrid model for short-term prediction of wind speed
Haize Hu, Yunyi Li, Xiangping Zhang, et al.
Pattern Recognition (2022) Vol. 127, pp. 108623-108623
Closed Access | Times Cited: 26
Condition monitoring and performance forecasting of wind turbines based on denoising autoencoder and novel convolutional neural networks
Xiongjie Jia, Yang Han, Yanjun Li, et al.
Energy Reports (2021) Vol. 7, pp. 6354-6365
Open Access | Times Cited: 28
Comprehensive comparison of various machine learning algorithms for short-term ozone concentration prediction
Ayman Yafouz, Nouar AlDahoul, Ahmed H. Birima, et al.
Alexandria Engineering Journal (2021) Vol. 61, Iss. 6, pp. 4607-4622
Open Access | Times Cited: 28
Wind power prediction based on PSO-Kalman
Daoqing Li, Xiaodong Yu, Shulin Liu, et al.
Energy Reports (2022) Vol. 8, pp. 958-968
Open Access | Times Cited: 21
Ensemble forecaster based on the combination of time-frequency analysis and machine learning strategies for very short-term wind speed prediction
Fermín Rodríguez, Sandra Alonso-Pérez, Ignacio Sánchez-Guardamino, et al.
Electric Power Systems Research (2022) Vol. 214, pp. 108863-108863
Open Access | Times Cited: 21
Multi-step ahead wind speed prediction based on a two-step decomposition technique and prediction model parameter optimization
He Wang, Min Xiong, Hongfeng Chen, et al.
Energy Reports (2022) Vol. 8, pp. 6086-6100
Open Access | Times Cited: 20
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