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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:

Machine Learning-based Time Series Modelling for Large-Scale Regional Wind Power Forecasting: a Case Study in Ontario, Canada
Hanin Alkabbani, Farzad Hourfar, Ali Ahmadian, et al.
Cleaner Energy Systems (2023) Vol. 5, pp. 100068-100068
Open Access | Times Cited: 9

Showing 9 citing articles:

A Comprehensive Review of Wind Power Prediction Based on Machine Learning: Models, Applications, and Challenges
Zongxu Liu, Hui Guo, Y. Zhang, et al.
Energies (2025) Vol. 18, Iss. 2, pp. 350-350
Open Access | Times Cited: 1
A spatiotemporal CNN-LSTM deep learning model for predicting soil temperature in diverse large-scale regional climates
Vahid Farhangmehr, Hanifeh Imanian, Abdolmajid Mohammadian, et al.
The Science of The Total Environment (2025) Vol. 968, pp. 178901-178901
Closed Access | Times Cited: 1
Artificial Neural Network Modeling in the Presence of Uncertainty for Predicting Hydrogenation Degree in Continuous Nitrile Butadiene Rubber Processing
Chandra Mouli R. Madhuranthakam, Farzad Hourfar, Ali Elkamel
Processes (2024) Vol. 12, Iss. 5, pp. 999-999
Open Access | Times Cited: 4
Machine Learning-Based Prediction of Pervaporation Permeation Using Physicochemical Properties of Permeant-Membrane and Process Conditions
Muhammad Mujiburohman, Marwen Elkamel, Farzad Hourfar, et al.
Heliyon (2025) Vol. 11, Iss. 4, pp. e42714-e42714
Open Access
WindDragon: automated deep learning for regional wind power forecasting
Julie Keisler, Étienne Le Naour
Environmental Data Science (2025) Vol. 4
Open Access
Application of four machine-learning methods to predict short-horizon wind energy
Doha Bouabdallaoui, Touria Haidi, Faissal Elmariami, et al.
Global Energy Interconnection (2023) Vol. 6, Iss. 6, pp. 726-737
Open Access | Times Cited: 9
Enhancing Wind Power Forecasting Accuracy with Hybrid Deep Learning and Teaching-Learning-Based Optimization
Mohd Herwan Sulaiman, Zuriani Mustaffa
Cleaner Energy Systems (2024) Vol. 9, pp. 100139-100139
Open Access | Times Cited: 3
Proactive failure warning for wind power forecast models based on volatility indicators analysis
Yunxiao Chen, Chaojing Lin, Yilan Zhang, et al.
Energy (2024) Vol. 305, pp. 132310-132310
Closed Access | Times Cited: 2
Combining Data Assimilation with Machine Learning to Predict the Regional Daily Leaf Area Index of Summer Maize (Zea mays L.)
Yongqiang Wang, Hui Zhou, Xiaoyi Ma, et al.
Agronomy (2023) Vol. 13, Iss. 11, pp. 2688-2688
Open Access | Times Cited: 4
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