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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:

Prediction of Electric Vehicles Charging Demand: A Transformer-Based Deep Learning Approach
Sahar Koohfar, Wubeshet Woldemariam, Amit Kumar
Sustainability (2023) Vol. 15, Iss. 3, pp. 2105-2105
Open Access | Times Cited: 45

Showing 1-25 of 45 citing articles:

Explainable spatiotemporal multi-task learning for electric vehicle charging demand prediction
Yitong Shang, Duo Li, Yang Li, et al.
Applied Energy (2025) Vol. 384, pp. 125460-125460
Closed Access | Times Cited: 3
Charge diagnostics and state estimation of Battery Energy Storage Systems through Transformer models
Rolando Gilbert Zequera, Anton Rassõlkin, Toomas Vaimann, et al.
IEEE Access (2025) Vol. 13, pp. 17733-17744
Open Access | Times Cited: 1
A comprehensive benchmark of machine learning-based algorithms for medium-term electric vehicle charging demand prediction
Ömer Can Tolun, Kasım Zor, Önder Tutsoy
The Journal of Supercomputing (2025) Vol. 81, Iss. 3
Open Access | Times Cited: 1
Review of Challenges and Opportunities in the Integration of Electric Vehicles to the Grid
G. Vishnu, K. Deepa, Ramprabhakar Jayaprakash, et al.
World Electric Vehicle Journal (2023) Vol. 14, Iss. 9, pp. 259-259
Open Access | Times Cited: 19
Seasonal electric vehicle forecasting model based on machine learning and deep learning techniques
Heba-Allah Ibrahim El-Azab, R.A. Swief, Noha H. El-Amary, et al.
Energy and AI (2023) Vol. 14, pp. 100285-100285
Open Access | Times Cited: 16
Performance Comparison of Deep Learning Approaches in Predicting EV Charging Demand
Sahar Koohfar, Wubeshet Woldemariam, Amit Kumar
Sustainability (2023) Vol. 15, Iss. 5, pp. 4258-4258
Open Access | Times Cited: 14
A data-driven approach to urban charging facility expansion based on bi-level optimization: A case study in a Chinese city
Jianing Cao, Yuhang Han, Nan Pan, et al.
Energy (2024) Vol. 300, pp. 131529-131529
Closed Access | Times Cited: 5
A novel thermal management system for lithium-ion battery modules combining indirect liquid-cooling with forced air-cooling: Deep learning approach
Chun Yang Guo, Mohammed W. Muhieldeen, Kah Hou Teng, et al.
Journal of Energy Storage (2024) Vol. 94, pp. 112434-112434
Closed Access | Times Cited: 5
Data-driven analysis and predictive modelling of hourly Air Quality Index (AQI) using deep learning techniques: a case study of Azamgarh, India
Asif Ansari, Abdur Rahman Quaff
Theoretical and Applied Climatology (2025) Vol. 156, Iss. 1
Closed Access
Artificial Intelligence in Lithium-Ion Battery Predictions
R. Shilpa, Karuppasamy Periyakaruppan, U. Mithra, et al.
Advances in computational intelligence and robotics book series (2025), pp. 203-236
Closed Access
Enhancing Charging Station Power Profiles: A Deep Learning Approach to Predicting Electric Vehicle Charging Demand
Yaqoob Ali, Jamila El Haini, Mohamed Errachidi, et al.
Smart Grids and Sustainable Energy (2025) Vol. 10, Iss. 1
Closed Access
Building energy efficiency: using machine learning algorithms to accurately predict heating load
Monireh Ahmadi
Asian Journal of Civil Engineering (2024) Vol. 25, Iss. 4, pp. 3129-3139
Closed Access | Times Cited: 4
Optimizing soybean biofuel blends for sustainable urban medium-duty commercial vehicles in India: an AI-driven approach
Upendra Rajak, Prem Kumar Chaurasiya, Tikendra Nath Verma, et al.
Environmental Science and Pollution Research (2024) Vol. 31, Iss. 22, pp. 32449-32463
Open Access | Times Cited: 4
A Comprehensive Study on Transformer-Based Time Series Forecasting
Di Wang
Advances in computational intelligence and robotics book series (2025), pp. 159-180
Closed Access
A hybrid Bayesian network-based deep learning approach combining climatic and reliability factors to forecast electric vehicle charging capacity
David Chunhu Li
Heliyon (2025) Vol. 11, Iss. 4, pp. e42483-e42483
Open Access
LTPNet Integration of Deep Learning and Environmental Decision Support Systems for Renewable Energy Demand Forecasting
Te Li, Min Zheng, Yan Zhou
Journal of Organizational and End User Computing (2025) Vol. 37, Iss. 1, pp. 1-29
Open Access
Coverage evaluation of public electric vehicle charging stations in Bangkok, Thailand using location-allocation model
Potsawat Oranpairoj, Ampol Karoonsoontawong, Kunnawee Kanitpong
Case Studies on Transport Policy (2025), pp. 101435-101435
Open Access
Interval Load Forecasting for Individual Households in the Presence of Electric Vehicle Charging
Raiden Skala, Mohamed Ahmed T. A. Elgalhud, Katarina Grolinger, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4093-4093
Open Access | Times Cited: 9
Optimizing Electric Vehicle (EV) Charging with Integrated Renewable Energy Sources: A Cloud-Based Forecasting Approach for Eco-Sustainability
Mohammad Aldossary, Hatem A. Alharbi, Nasir Ayub
Mathematics (2024) Vol. 12, Iss. 17, pp. 2627-2627
Open Access | Times Cited: 3
Self-supervised online learning algorithm for electric vehicle charging station demand and event prediction
Muhammad Ahsan Zamee, Dongjun Han, Hee-Jun Cha, et al.
Journal of Energy Storage (2023) Vol. 71, pp. 108189-108189
Closed Access | Times Cited: 8
Short-Term Forecasting of Electric Vehicle Load Using Time Series, Machine Learning, and Deep Learning Techniques
G. Vishnu, K. Deepa, Peeta Basa Pati, et al.
World Electric Vehicle Journal (2023) Vol. 14, Iss. 9, pp. 266-266
Open Access | Times Cited: 8
Waste heat recovery, efficient lighting, and proper insulation: a comprehensive study of energy consumption and savings in the residential sector
Saeed Momeni, Farhad Kooban, Saman Alipouri Niaz, et al.
Asian Journal of Civil Engineering (2023) Vol. 25, Iss. 3, pp. 2499-2508
Closed Access | Times Cited: 7
Comparative Analysis of Deep Learning Methods for Fault Avoidance and Predicting Demand in Electrical Distribution
Karla Schröder, Gonzalo Farías, S. Dormido-Canto, et al.
Energies (2024) Vol. 17, Iss. 11, pp. 2709-2709
Open Access | Times Cited: 1
Bi-Level Planning of Electric Vehicle Charging Stations Considering Spatial–Temporal Distribution Characteristics of Charging Loads in Uncertain Environments
Haiqing Gan, Wenjun Ruan, Mingshen Wang, et al.
Energies (2024) Vol. 17, Iss. 12, pp. 3004-3004
Open Access | Times Cited: 1
Electric Vehicle Charging Station Demand Prediction Model Deploying Data Slotting
Aditya Sreekumar, R. R. Lekshmi
Results in Engineering (2024) Vol. 24, pp. 103095-103095
Open Access | Times Cited: 1
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