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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:

Modified Particle Swarm Optimization with Attention-Based LSTM for Wind Power Prediction
Yiyang Sun, Xiangwen Wang, Junjie Yang
Energies (2022) Vol. 15, Iss. 12, pp. 4334-4334
Open Access | Times Cited: 34

Showing 1-25 of 34 citing articles:

Decomposition integration and error correction method for photovoltaic power forecasting
Guohui Li, Xuan Wei, Hong Yang
Measurement (2023) Vol. 208, pp. 112462-112462
Closed Access | Times Cited: 53
A short-term power prediction method for wind farm cluster based on the fusion of multi-source spatiotemporal feature information
Mao Yang, Chao Han, Wei Zhang, et al.
Energy (2024) Vol. 294, pp. 130770-130770
Closed Access | Times Cited: 17
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: 24
A hybrid wind speed prediction model using improved CEEMDAN and Autoformer model with auto-correlation mechanism
Bala Saibabu Bommidi, Kiran Teeparthi
Sustainable Energy Technologies and Assessments (2024) Vol. 64, pp. 103687-103687
Closed Access | Times Cited: 11
Machine Learning Approaches to Predict Electricity Production from Renewable Energy Sources
Adam Krechowicz, Maria Krechowicz, Katarzyna Poczęta
Energies (2022) Vol. 15, Iss. 23, pp. 9146-9146
Open Access | Times Cited: 26
Wind Power Short-Term Forecasting Method Based on LSTM and Multiple Error Correction
Zhengxuan Xiao, Fei Tang, Mengyuan Wang
Sustainability (2023) Vol. 15, Iss. 4, pp. 3798-3798
Open Access | Times Cited: 15
A D-stacking dual-fusion, spatio-temporal graph deep neural network based on a multi-integrated overlay for short-term wind-farm cluster power multi-step prediction
Zhijian Qu, Jian Li, Xinxing Hou, et al.
Energy (2023) Vol. 281, pp. 128289-128289
Closed Access | Times Cited: 15
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: 14
A Review of Wind Power Prediction Methods Based on Multi-Time Scales
Fan Li, Hongzhen Wang, Dan Wang, et al.
Energies (2025) Vol. 18, Iss. 7, pp. 1713-1713
Open Access
Rüzgâr Enerji Santral Üretim Tahmininde Kullanılan Meteorolojik Veriler için En Uygun İçsel Mod Fonksiyonunun Belirlenmesi: İzmir Örneği
İsrafil KARADÖL
Journal of Polytechnic (2025), pp. 1-1
Open Access
LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting
Te Li, Min Zheng, Yan Zhou
Journal of Organizational and End User Computing (2025) Vol. 37, Iss. 1, pp. 1-29
Open Access
Study on Gearbox Fault Warning Based on the Improved M-IALO-GRU Model
Yunhao Wang, Wenlei Sun, Han Liu, et al.
Applied Sciences (2025) Vol. 15, Iss. 6, pp. 3175-3175
Open Access
Design and Implementation of Short-Term Load Forecasting using STM
A. Balaguruperumal, P. Hemavarshini, Lakshan Damodharasami, et al.
Journal of Soft Computing Paradigm (2025) Vol. 7, Iss. 1, pp. 17-30
Open Access
Decomposition and Harris hawks optimized multivariate wind speed forecasting utilizing sequence2sequence-based spatiotemporal attention
Hassan Bashir, Muhammad Sibtain, Özge Hanay, et al.
Energy (2023) Vol. 278, pp. 127933-127933
Closed Access | Times Cited: 10
A survey of long short term memory and its associated models in sustainable wind energy predictive analytics
Sherry Garg, Rajalakshmi Krishnamurthi
Artificial Intelligence Review (2023) Vol. 56, Iss. S1, pp. 1149-1198
Closed Access | Times Cited: 9
Ultra-short-term wind power forecasting techniques: comparative analysis and future trends
Guangzheng Yu, Lingxu Shen, Qi Dong, et al.
Frontiers in Energy Research (2024) Vol. 11
Open Access | Times Cited: 3
Investigating the influence of clustering techniques and parameters on a hybrid PSO-driven ANFIS model for electricity prediction
Stephen Oladipo, Yanxia Sun, Abraham Amole
Deleted Journal (2024) Vol. 6, Iss. 5
Open Access | Times Cited: 3
Optimal control of hybrid wind-storage-hydrogen system based on wind power output prediction
Bo Yang, Ruyi Zheng, Jiarong Wang, et al.
Journal of Energy Storage (2024) Vol. 104, pp. 114432-114432
Closed Access | Times Cited: 3
Review of current artificial intelligence methods and metaheuristic algorithms for wind power prediction
Doha Bouabdallaoui, Touria Haidi, Mariam El Jaadi
Indonesian Journal of Electrical Engineering and Computer Science (2022) Vol. 29, Iss. 2, pp. 626-626
Open Access | Times Cited: 14
Analysis of the Impact of Clustering Techniques and Parameters on Evolutionary-Based Hybrid Models for Forecasting Electricity Consumption
Stephen Oladipo, Yanxia Sun, Abraham Amole
IEEE Access (2023) Vol. 11, pp. 82838-82856
Open Access | Times Cited: 7
Sizing PV and BESS for Grid-Connected Microgrid Resilience: A Data-Driven Hybrid Optimization Approach
Mahtab Murshed, Manohar Chamana, Konrad Schmitt, et al.
Energies (2023) Vol. 16, Iss. 21, pp. 7300-7300
Open Access | Times Cited: 7
ICEEMDAN-Informer-GWO: a hybrid model for accurate wind speed prediction
Bala Saibabu Bommidi, Kiran Teeparthi, Vinod Kumar Dulla Mallesham
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 23, pp. 34056-34081
Closed Access | Times Cited: 2
Accelerating optimal scheduling prediction in power system: A multi-faceted GAN-assisted prediction framework
Ali Peivand, Ehsan Azad‐Farsani, Hamid Reza Abdolmohammadi
Renewable Energy (2024) Vol. 230, pp. 120830-120830
Closed Access | Times Cited: 1
Adaptive expert fusion model for online wind power prediction
Renfang Wang, Jingtong Wu, Xu Cheng, et al.
Neural Networks (2024) Vol. 184, pp. 107022-107022
Open Access | Times Cited: 1
A hybrid model based on LSTM neural networks with attention mechanism for short-term wind power forecasting
Geovanny Marulanda, Jenny Cifuentes, Antonio Bello, et al.
Wind Engineering (2023)
Closed Access | Times Cited: 2
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