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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:

Load Forecasting with Machine Learning and Deep Learning Methods
Moisés Cordeiro-Costas, Daniel Villanueva, Pablo Eguía, et al.
Applied Sciences (2023) Vol. 13, Iss. 13, pp. 7933-7933
Open Access | Times Cited: 41

Showing 1-25 of 41 citing articles:

ENHANCING ENERGY EFFICIENCY WITH AI: A REVIEW OF MACHINE LEARNING MODELS IN ELECTRICITY DEMAND FORECASTING
Adebayo Olusegun Aderibigbe, Emmanuel Chigozie Ani, Peter Efosa Ohenhen, et al.
Engineering Science & Technology Journal (2023) Vol. 4, Iss. 6, pp. 341-356
Open Access | Times Cited: 28
Recent advancement in demand side energy management system for optimal energy utilization
Abraham Hizkiel Nebey
Energy Reports (2024) Vol. 11, pp. 5422-5435
Open Access | Times Cited: 9
Improved electric load forecasting using quantile long short-term memory network with dual attention mechanism
Shalin Shah, Ubaid Ahmed, Muhammad Bilal, et al.
Energy Reports (2025) Vol. 13, pp. 2343-2353
Closed Access
Explainable AI in thermal modelling enhancing precision in thermal gradient monitoring for additive manufacturing using LSTM networks
Ajmeera Kiran, Harish Kumar, S. N. Sivanandam, et al.
Thermal Science and Engineering Progress (2025), pp. 103465-103465
Closed Access
Accelerating FEM-Based Corrosion Predictions Using Machine Learning
David Montes de Oca Zapiain, Demitri Maestas, Matthew Roop, et al.
Journal of The Electrochemical Society (2024) Vol. 171, Iss. 1, pp. 011504-011504
Open Access | Times Cited: 5
An Optimum Load Forecasting Strategy (OLFS) for Smart Grids Based on Artificial Intelligence
Asmaa H. Rabie, Ahmed I. Saleh, Said H. Abd Elkhalik, et al.
Technologies (2024) Vol. 12, Iss. 2, pp. 19-19
Open Access | Times Cited: 5
NSGA-II based short-term building energy management using optimal LSTM-MLP forecasts
Moisés Cordeiro-Costas, Hugo Labandeira-Pérez, Daniel Villanueva, et al.
International Journal of Electrical Power & Energy Systems (2024) Vol. 159, pp. 110070-110070
Open Access | Times Cited: 5
Multi-Scale Building Load Forecasting Without Relying on Weather Forecast Data: A Temporal Convolutional Network, Long Short-Term Memory Network, and Self-Attention Mechanism Approach
Lanqian Yang, Jin‐Min Guo, Huili Tian, et al.
Buildings (2025) Vol. 15, Iss. 2, pp. 298-298
Open Access
Machine learning-based sales forecasting during crises: Evidence from a Turkish women's clothing retailer
Kiymet Tabak Kızgın, Selçuk Alp, Nezir Aydın, et al.
Science Progress (2025) Vol. 108, Iss. 1
Open Access
Contextual Background Estimation for Explainable AI in Temperature Prediction
Bartosz Szóstak, Rafał Doroz, Michael Märker
Applied Sciences (2025) Vol. 15, Iss. 3, pp. 1057-1057
Open Access
Advanced short-term load forecasting for residential demand response: An XGBoost-ANN ensemble approach
G. Harikrishnan, Sasidharan Sreedharan, Natarajan Chellappa
Electric Power Systems Research (2025) Vol. 242, pp. 111476-111476
Closed Access
Deep learning-based novel ensemble method with best score transferred-adaptive neuro fuzzy inference system for energy consumption prediction
Birce Dağkurs, İsmail Atacak
PeerJ Computer Science (2025) Vol. 11, pp. e2680-e2680
Open Access
Discrete-time state-of-charge estimator for latent heat thermal energy storage units based on a recurrent neural network
Héctor Bastida, Ivan De la Cruz‐Loredo, Pranaynil Saikia, et al.
Applied Energy (2024) Vol. 371, pp. 123526-123526
Open Access | Times Cited: 3
Analysis of aggregated load consumption forecasting in short, medium and long term horizons using Dynamic Mode Decomposition
Marc Carrillo Muñoz, Mònica Aragüés‐Peñalba, Antonio E. Saldaña-González
Energy Reports (2024) Vol. 12, pp. 1000-1013
Closed Access | Times Cited: 3
A Review of Research on Building Energy Consumption Prediction Models Based on Artificial Neural Networks
Qing Yin, Chunmiao Han, Ailin Li, et al.
Sustainability (2024) Vol. 16, Iss. 17, pp. 7805-7805
Open Access | Times Cited: 3
Advanced Digital Tools for Data-Informed and Performance-Driven Design: A Review of Building Energy Consumption Forecasting Models Based on Machine Learning
Andrea Giuseppe di Stefano, Matteo Francesco Ruta, Gabriele Masera
Applied Sciences (2023) Vol. 13, Iss. 24, pp. 12981-12981
Open Access | Times Cited: 9
A Multivariate Time Series Analysis of Electrical Load Forecasting Based on a Hybrid Feature Selection Approach and Explainable Deep Learning
Fatma Yaprakdal, Merve Varol Arısoy
Applied Sciences (2023) Vol. 13, Iss. 23, pp. 12946-12946
Open Access | Times Cited: 8
Enhanced efficiency in smart grid energy systems through advanced AI-based thermal modeling
Santhosh Krishna B V, S. Pauline, Sengottaian Sivakumar, et al.
Thermal Science and Engineering Progress (2024) Vol. 53, pp. 102765-102765
Closed Access | Times Cited: 2
PredXGBR: A Machine Learning Framework for Short-Term Electrical Load Prediction
Rifat Zabin, Khandaker Foysal Haque, Ahmed Abdelgawad
Electronics (2024) Vol. 13, Iss. 22, pp. 4521-4521
Open Access | Times Cited: 2
Applying Machine Learning in Retail Demand Prediction—A Comparison of Tree-Based Ensembles and Long Short-Term Memory-Based Deep Learning
Mehran Nasseri, Taha Falatouri, Patrick Brandtner, et al.
Applied Sciences (2023) Vol. 13, Iss. 19, pp. 11112-11112
Open Access | Times Cited: 6
Prophet–CEEMDAN–ARBiLSTM-Based Model for Short-Term Load Forecasting
Jindong Yang, Xiran Zhang, Wenhao Chen, et al.
Future Internet (2024) Vol. 16, Iss. 6, pp. 192-192
Open Access | Times Cited: 1
Effective Voting-Based Ensemble Learning for Segregated Load Forecasting With Low Sampling Data
Shahzeb Ahmad Khan, Attique Ur Rehman, Ammar Arshad, et al.
IEEE Access (2024) Vol. 12, pp. 84074-84087
Open Access | Times Cited: 1
Empowering Smart Cities: SARIMA Forecasting of Power Consumption in Tetouan's Urban Grid
Mouad Bensalah, Abdellatif Haïr
(2024), pp. 1-6
Closed Access | Times Cited: 1
Evaluation of Machine Learning Models for Predicting Cardiovascular Disease Based on Framingham Heart Study Data
Ruddy J. Suhatril, Rama Dian Syah, Matrissya Hermita, et al.
ILKOM Jurnal Ilmiah (2024) Vol. 16, Iss. 1, pp. 68-75
Open Access | Times Cited: 1
Medium-term feeder load forecasting and boosting peak accuracy prediction using the PWP-XGBoost model
Ansu Mathew, Rufaidah Chikte, Sajan K. Sadanandan, et al.
Electric Power Systems Research (2024) Vol. 237, pp. 111051-111051
Closed Access | Times Cited: 1
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