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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:

Wind power forecasting based on stacking ensemble model, decomposition and intelligent optimization algorithm
Yingchao Dong, Hongli Zhang, Cong Wang, et al.
Neurocomputing (2021) Vol. 462, pp. 169-184
Closed Access | Times Cited: 92

Showing 1-25 of 92 citing articles:

Point and interval forecasting of ultra-short-term wind power based on a data-driven method and hybrid deep learning model
Dongxiao Niu, Lijie Sun, Min Yu, et al.
Energy (2022) Vol. 254, pp. 124384-124384
Closed Access | Times Cited: 109
Electricity price forecasting with high penetration of renewable energy using attention-based LSTM network trained by crisscross optimization
Anbo Meng, Peng Wang, Guangsong Zhai, et al.
Energy (2022) Vol. 254, pp. 124212-124212
Closed Access | Times Cited: 92
IntelliSense technology in the new power systems
Haonan Xie, Meihui Jiang, Dongdong Zhang, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 177, pp. 113229-113229
Open Access | Times Cited: 42
A short-term wind power forecasting method based on multivariate signal decomposition and variable selection
Ting Yang, Zhenning Yang, Fei Li, et al.
Applied Energy (2024) Vol. 360, pp. 122759-122759
Closed Access | Times Cited: 26
Elman neural network considering dynamic time delay estimation for short-term forecasting of offshore wind power
Jing Huang, Rui Qin
Applied Energy (2024) Vol. 358, pp. 122671-122671
Closed Access | Times Cited: 18
Constrained Deep Reinforcement Transfer Learning for Short-Term Forecasting of Wind Discrepancies at Ocean Stations
Jun Zhang, Yaoran Chen, Hang Pan, et al.
Neurocomputing (2025), pp. 129491-129491
Closed Access | Times Cited: 2
A wind power forecasting method based on optimized decomposition prediction and error correction
Jun Li, Shuqing Zhang, Zhenning Yang
Electric Power Systems Research (2022) Vol. 208, pp. 107886-107886
Closed Access | Times Cited: 50
Improving teaching–learning-based-optimization algorithm by a distance-fitness learning strategy
Yunlang Xu, Yi Peng, Xinyi Su, et al.
Knowledge-Based Systems (2022) Vol. 257, pp. 108271-108271
Closed Access | Times Cited: 44
Wind power prediction based on outlier correction, ensemble reinforcement learning, and residual correction
Shi Yin, Hui Liu
Energy (2022) Vol. 250, pp. 123857-123857
Closed Access | Times Cited: 43
A compound framework incorporating improved outlier detection and correction, VMD, weight-based stacked generalization with enhanced DESMA for multi-step short-term wind speed forecasting
Wenlong Fu, Yuchen Fu, Bailing Li, et al.
Applied Energy (2023) Vol. 348, pp. 121587-121587
Closed Access | Times Cited: 32
Ensemble machine learning for modeling greenhouse gas emissions at different time scales from irrigated paddy fields
Zewei Jiang, Shihong Yang, Pete Smith, et al.
Field Crops Research (2023) Vol. 292, pp. 108821-108821
Closed Access | Times Cited: 30
Residential net load interval prediction based on stacking ensemble learning
Yan He, Hongli Zhang, Yingchao Dong, et al.
Energy (2024) Vol. 296, pp. 131134-131134
Closed Access | Times Cited: 13
Inversion of heavy metal content in soil using hyperspectral characteristic bands-based machine learning method
Zhiyong Zou, Qianlong Wang, Qingsong Wu, et al.
Journal of Environmental Management (2024) Vol. 355, pp. 120503-120503
Closed Access | Times Cited: 11
An emission predictive system for CO and NOx from gas turbine based on ensemble machine learning approach
Nikhil Pachauri
Fuel (2024) Vol. 366, pp. 131421-131421
Closed Access | Times Cited: 8
Enhanced load forecasting for distributed multi-energy system: A stacking ensemble learning method with deep reinforcement learning and model fusion
Xiaoxiao Ren, Xin Tian, Kai Wang, et al.
Energy (2025), pp. 135031-135031
Closed Access | Times Cited: 1
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
A novel multi-layer stacking ensemble wind power prediction model under Tensorflow deep learning framework considering feature enhancement and data hierarchy processing
Huaqing Wang, Zhongfu Tan, Yan Liang, et al.
Energy (2023) Vol. 286, pp. 129409-129409
Closed Access | Times Cited: 21
Research on the short-term wind power prediction with dual branch multi-source fusion strategy
Ling Tan, Yihe Chen, Jingming Xia, et al.
Energy (2024) Vol. 291, pp. 130402-130402
Closed Access | Times Cited: 6
An effective hybrid wind power forecasting model based on "decomposition-reconstruction-ensemble" strategy and wind resource matching
Yi Xiao, Sheng Wu, Chen He, et al.
Sustainable Energy Grids and Networks (2024) Vol. 38, pp. 101293-101293
Closed Access | Times Cited: 6
An Efficient and Interpretable Stacked Model for Wind Speed Estimation Based on Ensemble Learning Algorithms
Ankit Jha, Vansh Goel, Manish Kumar, et al.
Energy Technology (2024) Vol. 12, Iss. 6
Closed Access | Times Cited: 6
Applying an Improved Stacking Ensemble Model to Predict the Mortality of ICU Patients with Heart Failure
Chih‐Chou Chiu, Chung-Min Wu, Te-Nien Chien, et al.
Journal of Clinical Medicine (2022) Vol. 11, Iss. 21, pp. 6460-6460
Open Access | Times Cited: 26
Deep non-crossing probabilistic wind speed forecasting with multi-scale features
Runmin Zou, Mengmeng Song, Yun Wang, et al.
Energy Conversion and Management (2022) Vol. 257, pp. 115433-115433
Closed Access | Times Cited: 23
A novel network training approach for solving sample imbalance problem in wind power prediction
Anbo Meng, Zikang Xian, Hao Yin, et al.
Energy Conversion and Management (2023) Vol. 283, pp. 116935-116935
Closed Access | Times Cited: 16
Renewable Energy Forecasting Based on Stacking Ensemble Model and Al-Biruni Earth Radius Optimization Algorithm
Abdulrahman Abdullah Alghamdi, Abdelhameed Ibrahim‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬‬, El-Sayed M. El-kenawy, et al.
Energies (2023) Vol. 16, Iss. 3, pp. 1370-1370
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
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