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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 speed forecasting for wind farms: A method based on support vector regression
Guillermo Santamaría-Bonfil, Alberto Reyes, Carlos Gershenson
Renewable Energy (2015) Vol. 85, pp. 790-809
Closed Access | Times Cited: 342

Showing 1-25 of 342 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
Application of support vector machine models for forecasting solar and wind energy resources: A review
Alireza Zendehboudi, M.A. Baseer, R. Saidur
Journal of Cleaner Production (2018) Vol. 199, pp. 272-285
Closed Access | Times Cited: 508
Deep belief network based deterministic and probabilistic wind speed forecasting approach
Hai‐Kun Wang, G.B. Wang, Guangbo Li, et al.
Applied Energy (2016) Vol. 182, pp. 80-93
Closed Access | Times Cited: 459
Smart multi-step deep learning model for wind speed forecasting based on variational mode decomposition, singular spectrum analysis, LSTM network and ELM
Hui Liu, Xiwei Mi, Yanfei Li
Energy Conversion and Management (2018) Vol. 159, pp. 54-64
Closed Access | Times Cited: 429
Wind speed forecasting method based on deep learning strategy using empirical wavelet transform, long short term memory neural network and Elman neural network
Hui Liu, Xiwei Mi, Yan-fei Li
Energy Conversion and Management (2017) Vol. 156, pp. 498-514
Closed Access | Times Cited: 420
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: 326
Short-term offshore wind speed forecast by seasonal ARIMA - A comparison against GRU and LSTM
Xiaolei Liu, Zi Lin, Zi‐Ming Feng
Energy (2021) Vol. 227, pp. 120492-120492
Open Access | Times Cited: 307
Review of distributed generation (DG) system planning and optimisation techniques: Comparison of numerical and mathematical modelling methods
Wai Lip Theo, Jeng Shiun Lim, Wai Shin Ho, et al.
Renewable and Sustainable Energy Reviews (2016) Vol. 67, pp. 531-573
Closed Access | Times Cited: 267
Application of hybrid model based on empirical mode decomposition, novel recurrent neural networks and the ARIMA to wind speed prediction
Ming-De Liu, Lin Ding, Yulong Bai
Energy Conversion and Management (2021) Vol. 233, pp. 113917-113917
Closed Access | Times Cited: 263
Prediction of wind speed and wind direction using artificial neural network, support vector regression and adaptive neuro-fuzzy inference system
Ali Khosravi, R.N.N. Koury, Luiz Machado, et al.
Sustainable Energy Technologies and Assessments (2018) Vol. 25, pp. 146-160
Closed Access | Times Cited: 257
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: 252
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
An improved neural network-based approach for short-term wind speed and power forecast
G. W. Chang, H. J. Lu, Y.-R. Chang, et al.
Renewable Energy (2016) Vol. 105, pp. 301-311
Closed Access | Times Cited: 225
A novel hybrid forecasting system of wind speed based on a newly developed multi-objective sine cosine algorithm
Jianzhou Wang, Wendong Yang, Pei Du, et al.
Energy Conversion and Management (2018) Vol. 163, pp. 134-150
Closed Access | Times Cited: 206
Time-series prediction of wind speed using machine learning algorithms: A case study Osorio wind farm, Brazil
Ali Khosravi, Luiz Machado, Raphael Nunes
Applied Energy (2018) Vol. 224, pp. 550-566
Closed Access | Times Cited: 201
What can machine learning do for seismic data processing? An interpolation application
Yongna Jia, Jianwei Ma
Geophysics (2017) Vol. 82, Iss. 3, pp. V163-V177
Closed Access | Times Cited: 194
Short-term wind speed forecasting using recurrent neural networks with error correction
Jikai Duan, Hongchao Zuo, Yulong Bai, et al.
Energy (2020) Vol. 217, pp. 119397-119397
Closed Access | Times Cited: 193
A generalized dynamic fuzzy neural network based on singular spectrum analysis optimized by brain storm optimization for short-term wind speed forecasting
Xuejiao Ma, Yu Jin, Qingli Dong
Applied Soft Computing (2017) Vol. 54, pp. 296-312
Closed Access | Times Cited: 188
Gaussian Process Regression for numerical wind speed prediction enhancement
Haoshu Cai, Xiaodong Jia, Jianshe Feng, et al.
Renewable Energy (2019) Vol. 146, pp. 2112-2123
Closed Access | Times Cited: 166
Recent advances in hot tearing during casting of aluminium alloys
Yue Li, Hongxiang Li, L. Katgerman, et al.
Progress in Materials Science (2020) Vol. 117, pp. 100741-100741
Open Access | Times Cited: 165
Short-term wind speed prediction based on LMD and improved FA optimized combined kernel function LSSVM
Zhongda Tian
Engineering Applications of Artificial Intelligence (2020) Vol. 91, pp. 103573-103573
Closed Access | Times Cited: 159
A novel deep learning ensemble model with data denoising for short-term wind speed forecasting
Zhiyun Peng, Sui Peng, Lidan Fu, et al.
Energy Conversion and Management (2020) Vol. 207, pp. 112524-112524
Closed Access | Times Cited: 144
Ultra‐short‐term multi‐step wind power forecasting based on CNN‐LSTM
Qianyu Wu, Fei Guan, Chen Lv, et al.
IET Renewable Power Generation (2021) Vol. 15, Iss. 5, pp. 1019-1029
Open Access | Times Cited: 135
Multi-step-ahead wind speed forecasting based on a hybrid decomposition method and temporal convolutional networks
Dan Li, Fuxin Jiang, Min Chen, et al.
Energy (2021) Vol. 238, pp. 121981-121981
Closed Access | Times Cited: 135
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: 131
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