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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 cascaded deep learning wind power prediction approach based on a two-layer of mode decomposition
Hao Yin, Zuhong Ou, Shengquan Huang, et al.
Energy (2019) Vol. 189, pp. 116316-116316
Closed Access | Times Cited: 90

Showing 26-50 of 90 citing articles:

Short-term wind speed forecasting based on adaptive secondary decomposition and robust temporal convolutional network
Guowei Zhang, Yi Zhang, Hui Wang, et al.
Energy (2023) Vol. 288, pp. 129618-129618
Closed Access | Times Cited: 19
Advanced series decomposition with a gated recurrent unit and graph convolutional neural network for non-stationary data patterns
Huimin Han, Harold Neira-Molina, Asad Khan, et al.
Journal of Cloud Computing Advances Systems and Applications (2024) Vol. 13, Iss. 1
Open Access | Times Cited: 7
Wind speed and wind power forecasting models
M. Lydia, G. Edwin Prem Kumar, R. Akash
Energy & Environment (2024)
Closed Access | Times Cited: 7
A reconstruction-based secondary decomposition-ensemble framework for wind power forecasting
Runkun Cheng, Di Yang, Da Liu, et al.
Energy (2024) Vol. 308, pp. 132895-132895
Closed Access | Times Cited: 7
Review of several key processes in wind power forecasting: Mathematical formulations, scientific problems, and logical relations
Mao Yang, Y. Huang, Chuanyu Xu, et al.
Applied Energy (2024) Vol. 377, pp. 124631-124631
Closed Access | Times Cited: 7
Development and trending of deep learning methods for wind power predictions
Hong Liu, Zijun Zhang
Artificial Intelligence Review (2024) Vol. 57, Iss. 5
Open Access | Times Cited: 6
Modeling and performance evaluation of wind turbine based on ant colony optimization-extreme learning machine
Xiaoqiang Wen
Applied Soft Computing (2020) Vol. 94, pp. 106476-106476
Closed Access | Times Cited: 42
A novel asexual-reproduction evolutionary neural network for wind power prediction based on generative adversarial networks
Hao Yin, Zuhong Ou, Zibin Zhu, et al.
Energy Conversion and Management (2021) Vol. 247, pp. 114714-114714
Closed Access | Times Cited: 37
Advanced Ensemble Methods Using Machine Learning and Deep Learning for One-Day-Ahead Forecasts of Electric Energy Production in Wind Farms
P. Piotrowski, D. Baczyński, Marcin Kopyt, et al.
Energies (2022) Vol. 15, Iss. 4, pp. 1252-1252
Open Access | Times Cited: 27
Evaluation Metrics for Wind Power Forecasts: A Comprehensive Review and Statistical Analysis of Errors
P. Piotrowski, Inajara Rutyna, D. Baczyński, et al.
Energies (2022) Vol. 15, Iss. 24, pp. 9657-9657
Open Access | Times Cited: 26
Multi-step-ahead significant wave height prediction using a hybrid model based on an innovative two-layer decomposition framework and LSTM
Fu Yang, Feixiang Ying, Lingling Huang, et al.
Renewable Energy (2022) Vol. 203, pp. 455-472
Closed Access | Times Cited: 26
Wind Power Forecasting Using Optimized Dendritic Neural Model Based on Seagull Optimization Algorithm and Aquila Optimizer
Mohammed A. A. Al‐qaness, Ahmed A. Ewees, Mohamed Abd Elaziz, et al.
Energies (2022) Vol. 15, Iss. 24, pp. 9261-9261
Open 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
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 novel multi-gradient evolutionary deep learning approach for few-shot wind power prediction using time-series GAN
Anbo Meng, Hai‐Tao Zhang, Hao Yin, et al.
Energy (2023) Vol. 283, pp. 129139-129139
Closed Access | Times Cited: 15
An Adaptive Hybrid Model for Wind Power Prediction Based on the IVMD-FE-Ad-Informer
Yuqian Tian, Dazhi Wang, Guolin Zhou, et al.
Entropy (2023) Vol. 25, Iss. 4, pp. 647-647
Open Access | Times Cited: 13
Deep Learning for Variable Renewable Energy: A Systematic Review
Janice Klaiber, Clemens van Dinther
ACM Computing Surveys (2023) Vol. 56, Iss. 1, pp. 1-37
Closed Access | Times Cited: 13
Carbon emissions trading price forecasting based on temporal-spatial multidimensional collaborative attention network and segment imbalance regression
Hao Yin, Yiding Yin, Hanhong Li, et al.
Applied Energy (2024) Vol. 377, pp. 124357-124357
Closed Access | Times Cited: 5
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
On wavelet transform based convolutional neural network and twin support vector regression for wind power ramp event prediction
Harsh S. Dhiman, Dipankar Deb, Josep M. Guerrero
Sustainable Computing Informatics and Systems (2022) Vol. 36, pp. 100795-100795
Open Access | Times Cited: 20
An adaptive variational mode decomposition for wind power prediction using convolutional block attention deep learning network
Anbo Meng, Zhifeng Xie, Jianqiang Luo, et al.
Energy (2023) Vol. 282, pp. 128945-128945
Closed Access | Times Cited: 12
SOC estimation method for power lithium batteries in energy storage system
Zewen Li, Yuanliang Fan, Han Wu, et al.
Journal of Physics Conference Series (2025) Vol. 2936, Iss. 1, pp. 012030-012030
Open Access
Short-Term Wind Power Prediction Based on Data Reconstruction and Improved Extreme Learning Machine
Haobo Li, Hairong Zou
Arabian Journal for Science and Engineering (2022) Vol. 47, Iss. 3, pp. 3669-3682
Closed Access | Times Cited: 16
An ensemble model for short-term wind power prediction based on EEMD-GRU-MC
Peilin Wang, Chengguo Su, Li Li, et al.
Frontiers in Energy Research (2024) Vol. 11
Open Access | Times Cited: 3
A Novel Hybrid Deep Learning Model for Photovoltaic Power Forecasting Based on Feature Extraction and BiLSTM
Wenshuai Lin, Bin Zhang, Renquan Lu
IEEJ Transactions on Electrical and Electronic Engineering (2024) Vol. 19, Iss. 3, pp. 305-317
Closed Access | Times Cited: 3

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