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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:

Short-term wind power forecasting using adaptive neuro-fuzzy inference system combined with evolutionary particle swarm optimization, wavelet transform and mutual information
Gerardo J. Osório, J.C.O. Matias, João P. S. Catalào
Renewable Energy (2014) Vol. 75, pp. 301-307
Closed Access | Times Cited: 206

Showing 1-25 of 206 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: 538
Applications of fuzzy logic in renewable energy systems – A review
L. Suganthi, S. Iniyan, Anand A. Samuel
Renewable and Sustainable Energy Reviews (2015) Vol. 48, pp. 585-607
Closed Access | Times Cited: 484
Spatio-Temporal Graph Deep Neural Network for Short-Term Wind Speed Forecasting
Mahdi Khodayar, Jianhui Wang
IEEE Transactions on Sustainable Energy (2018) Vol. 10, Iss. 2, pp. 670-681
Closed Access | Times Cited: 375
Short-term wind power forecasting based on support vector machine with improved dragonfly algorithm
Lin Li, Xue Zhao, Ming‐Lang Tseng, et al.
Journal of Cleaner Production (2019) Vol. 242, pp. 118447-118447
Closed Access | Times Cited: 358
Hour-ahead wind power forecast based on random forests
Ali Lahouar, Jaleleddine Ben Hadj Slama
Renewable Energy (2017) Vol. 109, pp. 529-541
Closed Access | Times Cited: 322
Data processing strategies in wind energy forecasting models and applications: A comprehensive review
Hui Liu, Chao Chen
Applied Energy (2019) Vol. 249, pp. 392-408
Closed Access | Times Cited: 295
Forecasting methods in energy planning models
Kumar Biswajit Debnath, Monjur Mourshed
Renewable and Sustainable Energy Reviews (2018) Vol. 88, pp. 297-325
Open Access | Times Cited: 293
Forecasting energy consumption using ensemble ARIMA–ANFIS hybrid algorithm
Sasan Barak, S. Saeedeh Sadegh
International Journal of Electrical Power & Energy Systems (2016) Vol. 82, pp. 92-104
Open Access | Times Cited: 290
A robust combination approach for short-term wind speed forecasting and analysis – Combination of the ARIMA (Autoregressive Integrated Moving Average), ELM (Extreme Learning Machine), SVM (Support Vector Machine) and LSSVM (Least Square SVM) forecasts using a GPR (Gaussian Process Regression) model
Jianzhou Wang, Jianming Hu
Energy (2015) Vol. 93, pp. 41-56
Closed Access | Times Cited: 289
Deterministic wind energy forecasting: A review of intelligent predictors and auxiliary methods
Hui Liu, Chao Chen, Xinwei Lv, et al.
Energy Conversion and Management (2019) Vol. 195, pp. 328-345
Closed Access | Times Cited: 250
A compound structure of ELM based on feature selection and parameter optimization using hybrid backtracking search algorithm for wind speed forecasting
Chu Zhang, Jianzhong Zhou, Chaoshun Li, et al.
Energy Conversion and Management (2017) Vol. 143, pp. 360-376
Closed Access | Times Cited: 249
Current status of wind energy forecasting and a hybrid method for hourly predictions
İnci Okumuş, Ali Dinler
Energy Conversion and Management (2016) Vol. 123, pp. 362-371
Closed Access | Times Cited: 244
A new intelligent method based on combination of VMD and ELM for short term wind power forecasting
Ali Akbar Abdoos
Neurocomputing (2016) Vol. 203, pp. 111-120
Closed Access | Times Cited: 234
A novel hybrid model based on VMD-WT and PCA-BP-RBF neural network for short-term wind speed forecasting
Yagang Zhang, Bing Chen, Guifang Pan, et al.
Energy Conversion and Management (2019) Vol. 195, pp. 180-197
Closed Access | Times Cited: 222
Predictive Deep Boltzmann Machine for Multiperiod Wind Speed Forecasting
Chun-Yang Zhang, C. L. Philip Chen, Min Gan, et al.
IEEE Transactions on Sustainable Energy (2015) Vol. 6, Iss. 4, pp. 1416-1425
Closed Access | Times Cited: 208
RETRACTED: Artificial neural networks applications in wind energy systems: a review
Raşit Ata
Renewable and Sustainable Energy Reviews (2015) Vol. 49, pp. 534-562
Closed Access | Times Cited: 208
Short-term wind speed prediction using empirical wavelet transform and Gaussian process regression
Jianming Hu, Jianzhou Wang
Energy (2015) Vol. 93, pp. 1456-1466
Closed Access | Times Cited: 199
A novel bidirectional mechanism based on time series model for wind power forecasting
Yongning Zhao, Lin Ye, Zhi Li, et al.
Applied Energy (2016) Vol. 177, pp. 793-803
Open Access | Times Cited: 198
Ensemble empirical mode decomposition based adaptive wavelet neural network method for wind speed prediction
Santhosh Madasthu, Chintham Venkaiah, D. M. Vinod Kumar
Energy Conversion and Management (2018) Vol. 168, pp. 482-493
Closed Access | Times Cited: 188
Prediction interval of wind power using parameter optimized Beta distribution based LSTM model
Xiaohui Yuan, Chen Chen, Min Jiang, et al.
Applied Soft Computing (2019) Vol. 82, pp. 105550-105550
Closed Access | Times Cited: 168
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: 154
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: 129
A novel framework for ultra-short-term interval wind power prediction based on RF-WOA-VMD and BiGRU optimized by the attention mechanism
Min Yu, Dongxiao Niu, Tian Gao, et al.
Energy (2023) Vol. 269, pp. 126738-126738
Closed Access | Times Cited: 122
A novel DWTimesNet-based short-term multi-step wind power forecasting model using feature selection and auto-tuning methods
Chu Zhang, Yuhan Wang, Yongyan Fu, et al.
Energy Conversion and Management (2024) Vol. 301, pp. 118045-118045
Closed Access | Times Cited: 22
Probability density forecasting of wind power using quantile regression neural network and kernel density estimation
Yaoyao He, Haiyan Li
Energy Conversion and Management (2018) Vol. 164, pp. 374-384
Closed Access | Times Cited: 158
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