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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 novel non-linear combination system for short-term wind speed forecast
Jianzhou Wang, Shiqi Wang, Wendong Yang
Renewable Energy (2019) Vol. 143, pp. 1172-1192
Closed Access | Times Cited: 60

Showing 1-25 of 60 citing articles:

A review of wind speed and wind power forecasting with deep neural networks
Yun Wang, Runmin Zou, Fang Liu, et al.
Applied Energy (2021) Vol. 304, pp. 117766-117766
Closed Access | Times Cited: 545
A review on multi-objective optimization framework in wind energy forecasting techniques and applications
Hui Liu, Ye Li, Zhu Duan, et al.
Energy Conversion and Management (2020) Vol. 224, pp. 113324-113324
Closed Access | Times Cited: 156
Interpretable wind speed prediction with multivariate time series and temporal fusion transformers
Binrong Wu, Lin Wang, Yu‐Rong Zeng
Energy (2022) Vol. 252, pp. 123990-123990
Closed Access | Times Cited: 147
Review of meta-heuristic algorithms for wind power prediction: Methodologies, applications and challenges
Peng Lu, Lin Ye, Yongning Zhao, et al.
Applied Energy (2021) Vol. 301, pp. 117446-117446
Closed Access | Times Cited: 131
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: 15
Modes decomposition forecasting approach for ultra-short-term wind speed
Zhongda Tian
Applied Soft Computing (2021) Vol. 105, pp. 107303-107303
Closed Access | Times Cited: 77
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: 77
Deterministic and probabilistic wind speed forecasting with de-noising-reconstruction strategy and quantile regression based algorithm
Jianming Hu, Jiani Heng, Jiemei Wen, et al.
Renewable Energy (2020) Vol. 162, pp. 1208-1226
Closed Access | Times Cited: 72
Short-Term Wind Power Prediction via Spatial Temporal Analysis and Deep Residual Networks
Huajin Li
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 66
Numerical weather prediction enhanced wind power forecasting: Rank ensemble and probabilistic fluctuation awareness
Chenyu Liu, Xuemin Zhang, Shengwei Mei, et al.
Applied Energy (2022) Vol. 313, pp. 118769-118769
Closed Access | Times Cited: 50
The Orb-Weaving Spider Algorithm for Training of Recurrent Neural Networks
А С Михалев, В С Тынченко, Vladimir Nelyub, et al.
Symmetry (2022) Vol. 14, Iss. 10, pp. 2036-2036
Open Access | Times Cited: 46
Wind speed forecasting based on model selection, fuzzy cluster, and multi-objective algorithm and wind energy simulation by Betz's theory
Shenghui Zhang, Chen Wang, Peng Liao, et al.
Expert Systems with Applications (2022) Vol. 193, pp. 116509-116509
Closed Access | Times Cited: 45
Innovative ensemble system based on mixed frequency modeling for wind speed point and interval forecasting
Wendong Yang, Mengying Hao, Hao Yan
Information Sciences (2022) Vol. 622, pp. 560-586
Closed Access | Times Cited: 41
Offshore wind speed assessment with statistical and attention-based neural network methods based on STL decomposition
Li Xu, Yanxia Ou, Jingjing Cai, et al.
Renewable Energy (2023) Vol. 216, pp. 119097-119097
Closed Access | Times Cited: 29
Short-term wind power forecasting by stacked recurrent neural networks with parametric sine activation function
Xin Liu, Jun Zhou, Huimin Qian
Electric Power Systems Research (2020) Vol. 192, pp. 107011-107011
Closed Access | Times Cited: 68
A Hybrid System Based on LSTM for Short-Term Power Load Forecasting
Yu Jin, Honggang Guo, Jianzhou Wang, et al.
Energies (2020) Vol. 13, Iss. 23, pp. 6241-6241
Open Access | Times Cited: 67
A novel multiscale forecasting model for crude oil price time series
Ranran Li, Yucai Hu, Jiani Heng, et al.
Technological Forecasting and Social Change (2021) Vol. 173, pp. 121181-121181
Closed Access | Times Cited: 55
Current status of hybrid structures in wind forecasting
Mehrnaz Ahmadi, Mehdi Khashei
Engineering Applications of Artificial Intelligence (2020) Vol. 99, pp. 104133-104133
Closed Access | Times Cited: 54
Short-term wind speed forecasting system based on multivariate time series and multi-objective optimization
Zhihao Shang, Zhaoshuang He, Yao Chen, et al.
Energy (2021) Vol. 238, pp. 122024-122024
Closed Access | Times Cited: 52
Hybrid model based on VMD decomposition, clustering analysis, long short memory network, ensemble learning and error complementation for short-term wind speed forecasting assisted by Flink platform
Zexian Sun, Mingyu Zhao, Guohong Zhao
Energy (2022) Vol. 261, pp. 125248-125248
Closed Access | Times Cited: 35
A physics-inspired neural network model for short-term wind power prediction considering wake effects
Naizhi Guo, Ke-Zhong Shi, Bo Li, et al.
Energy (2022) Vol. 261, pp. 125208-125208
Closed Access | Times Cited: 30
A novel integrated method based on a machine learning model for estimating evapotranspiration in dryland
Tonglin Fu, Xinrong Li, Rongliang Jia, et al.
Journal of Hydrology (2021) Vol. 603, pp. 126881-126881
Closed Access | Times Cited: 34
The Potential of Machine Learning for Wind Speed and Direction Short-Term Forecasting: A Systematic Review
Décio Alves, Fábio Mendonça, Sheikh Shanawaz Mostafa, et al.
Computers (2023) Vol. 12, Iss. 10, pp. 206-206
Open Access | Times Cited: 13
Advancing Renewable Energy Forecasting: A Comprehensive Review of Renewable Energy Forecasting Methods
Rita Teixeira, Adelaide Cerveira, E. J. Solteiro Pires, et al.
Energies (2024) Vol. 17, Iss. 14, pp. 3480-3480
Open Access | Times Cited: 5
Developing a dual-modal surrogate model training framework for building performance prediction in early design stage
Zhen Han, Gang Liu, Lihua Zhang, et al.
Energy and Buildings (2025), pp. 115307-115307
Closed Access
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