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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 new short-term wind speed forecasting method based on fine-tuned LSTM neural network and optimal input sets
Gholamreza Memarzadeh, Farshid Keynia
Energy Conversion and Management (2020) Vol. 213, pp. 112824-112824
Closed Access | Times Cited: 251

Showing 1-25 of 251 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
Wind power forecasting – A data-driven method along with gated recurrent neural network
Adam Kisvari, Zi Lin, Xiaolei Liu
Renewable Energy (2020) Vol. 163, pp. 1895-1909
Open Access | Times Cited: 277
A review and taxonomy of wind and solar energy forecasting methods based on deep learning
Ghadah Alkhayat, Rashid Mehmood
Energy and AI (2021) Vol. 4, pp. 100060-100060
Open Access | Times Cited: 204
A deep learning-based evolutionary model for short-term wind speed forecasting: A case study of the Lillgrund offshore wind farm
Mehdi Neshat, Meysam Majidi Nezhad, Ehsan Abbasnejad, et al.
Energy Conversion and Management (2021) Vol. 236, pp. 114002-114002
Closed Access | Times Cited: 179
Short-term electricity load and price forecasting by a new optimal LSTM-NN based prediction algorithm
Gholamreza Memarzadeh, Farshid Keynia
Electric Power Systems Research (2020) Vol. 192, pp. 106995-106995
Closed Access | Times Cited: 177
HBO-LSTM: Optimized long short term memory with heap-based optimizer for wind power forecasting
Ahmed A. Ewees, Mohammed A. A. Al‐qaness, Laith Abualigah, et al.
Energy Conversion and Management (2022) Vol. 268, pp. 116022-116022
Closed Access | Times Cited: 114
A novel wind speed prediction strategy based on Bi-LSTM, MOOFADA and transfer learning for centralized control centers
Tao Liang, Qing Zhao, Qingzhao Lv, et al.
Energy (2021) Vol. 230, pp. 120904-120904
Closed Access | Times Cited: 102
Deep learning combined wind speed forecasting with hybrid time series decomposition and multi-objective parameter optimization
Sheng-Xiang Lv, Lin Wang
Applied Energy (2022) Vol. 311, pp. 118674-118674
Closed Access | Times Cited: 87
Combining autoregressive integrated moving average with Long Short-Term Memory neural network and optimisation algorithms for predicting ground water level
Zohreh Sheikh Khozani, Fatemeh Barzegari Banadkooki, Mohammad Ehteram, et al.
Journal of Cleaner Production (2022) Vol. 348, pp. 131224-131224
Closed Access | Times Cited: 86
A combined short-term wind speed forecasting model based on CNN–RNN and linear regression optimization considering error
Jikai Duan, Mingheng Chang, Xiangyue Chen, et al.
Renewable Energy (2022) Vol. 200, pp. 788-808
Closed Access | Times Cited: 79
A CGRU multi-step wind speed forecasting model based on multi-label specific XGBoost feature selection and secondary decomposition
Zheyong Jiang, Jinxing Che, Mingjun He, et al.
Renewable Energy (2022) Vol. 203, pp. 802-827
Closed Access | Times Cited: 71
A convolutional Transformer-based truncated Gaussian density network with data denoising for wind speed forecasting
Yun Wang, Houhua Xu, Mengmeng Song, et al.
Applied Energy (2023) Vol. 333, pp. 120601-120601
Closed Access | Times Cited: 62
Deep learning-based multistep ahead wind speed and power generation forecasting using direct method
Maryam Yaghoubirad, Narjes Azizi, Meisam Farajollahi, et al.
Energy Conversion and Management (2023) Vol. 281, pp. 116760-116760
Closed Access | Times Cited: 50
An imputation and decomposition algorithms based integrated approach with bidirectional LSTM neural network for wind speed prediction
Karan Sareen, Bijaya Ketan Panigrahi, Tushar Shikhola, et al.
Energy (2023) Vol. 278, pp. 127799-127799
Closed Access | Times Cited: 49
CNN-LSTM vs. LSTM-CNN to Predict Power Flow Direction: A Case Study of the High-Voltage Subnet of Northeast Germany
Fachrizal Aksan, Yang Li, Vishnu Suresh, et al.
Sensors (2023) Vol. 23, Iss. 2, pp. 901-901
Open Access | Times Cited: 46
Optimized Forecasting Model to Improve the Accuracy of Very Short-Term Wind Power Prediction
Md. Alamgir Hossain, Evan Gray, Junwei Lu, et al.
IEEE Transactions on Industrial Informatics (2023) Vol. 19, Iss. 10, pp. 10145-10159
Open Access | Times Cited: 43
A novel ensemble system for short-term wind speed forecasting based on hybrid decomposition approach and artificial intelligence models optimized by self-attention mechanism
Junheng Pang, Sheng Dong
Energy Conversion and Management (2024) Vol. 307, pp. 118343-118343
Closed Access | Times Cited: 22
Arctic short-term wind speed forecasting based on CNN-LSTM model with CEEMDAN
Qingyang Li, Guosong Wang, Xinrong Wu, et al.
Energy (2024) Vol. 299, pp. 131448-131448
Closed Access | Times Cited: 19
A hybrid wind speed forecasting model with two-stage data processing based on adaptive neuro-fuzzy inference systems and deep learning algorithms
Zhongda Tian, D. H. Wei
Earth Science Informatics (2025) Vol. 18, Iss. 1
Closed Access | Times Cited: 2
Machine learning-based evolution of water quality prediction model: an integrated robust framework for comparative application on periodic return and jitter data
Xizhi Nong, Yi He, Lihua Chen, et al.
Environmental Pollution (2025), pp. 125834-125834
Closed Access | Times Cited: 2
Reliability analysis of wind turbine gearboxes: past, progress and future prospects
Debiao Meng, Peng Nie, Shiyuan Yang, et al.
International Journal of Structural Integrity (2025)
Closed Access | Times Cited: 1
Deep learning in electrical utility industry: A comprehensive review of a decade of research
Manohar Mishra, Janmenjoy Nayak, Bighnaraj Naik, et al.
Engineering Applications of Artificial Intelligence (2020) Vol. 96, pp. 104000-104000
Closed Access | Times Cited: 93
Modeling and predicting the electricity production in hydropower using conjunction of wavelet transform, long short-term memory and random forest models
Mehdi Zolfaghari, Mohammad Reza Golabi
Renewable Energy (2021) Vol. 170, pp. 1367-1381
Closed Access | Times Cited: 76
Sparse Gaussian process regression for multi-step ahead forecasting of wind gusts combining numerical weather predictions and on-site measurements
Hao Wang, Yiming Zhang, Jianxiao Mao
Journal of Wind Engineering and Industrial Aerodynamics (2021) Vol. 220, pp. 104873-104873
Closed Access | Times Cited: 69
A novel approach to multi-horizon wind power forecasting based on deep neural architecture
Dominik Putz, Michael Gumhalter, Hans Auer
Renewable Energy (2021) Vol. 178, pp. 494-505
Closed Access | Times Cited: 65
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