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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:

Current status, challenges, and prospects of data-driven urban energy modeling: A review of machine learning methods
Prajowal Manandhar, Hasan Rafiq, Edwin Rodríguez-Ubiñas
Energy Reports (2023) Vol. 9, pp. 2757-2776
Open Access | Times Cited: 30

Showing 1-25 of 30 citing articles:

Prospects and Challenges of the Machine Learning and Data-Driven Methods for the Predictive Analysis of Power Systems: A Review
Wadim Striełkowski, Andrey Vlasov, Kirill Selivanov, et al.
Energies (2023) Vol. 16, Iss. 10, pp. 4025-4025
Open Access | Times Cited: 56
Urban building energy performance prediction and retrofit analysis using data-driven machine learning approach
Usman Ali, Sobia Bano, Mohammad Haris Shamsi, et al.
Energy and Buildings (2023) Vol. 303, pp. 113768-113768
Open Access | Times Cited: 50
A review of current methods and challenges of advanced deep learning-based non-intrusive load monitoring (NILM) in residential context
Hasan Rafiq, Prajowal Manandhar, Edwin Rodríguez-Ubiñas, et al.
Energy and Buildings (2024) Vol. 305, pp. 113890-113890
Closed Access | Times Cited: 20
Multivariate machine learning algorithms for energy demand forecasting and load behavior analysis
Farhan Hussain, M. Hasanuzzaman, Nasrudin Abd Rahim
Energy Conversion and Management X (2025), pp. 100903-100903
Open Access | Times Cited: 4
Data-driven modelling for assessing trophic status in marine ecosystems using machine learning approaches
Md Galal Uddin, Stephen Nash, Azizur Rahman, et al.
Environmental Research (2023) Vol. 242, pp. 117755-117755
Open Access | Times Cited: 38
Modeling and forecasting electricity consumption amid the COVID-19 pandemic: Machine learning vs. nonlinear econometric time series models
Lanouar Charfeddine, Esmat Zaidan, Ahmad Qadeib Alban, et al.
Sustainable Cities and Society (2023) Vol. 98, pp. 104860-104860
Open Access | Times Cited: 28
Systematic review of the efficacy of data-driven urban building energy models during extreme heat in cities: Current trends and future outlook
Nilabhra Mondal, Prashant Anand, Ansar Khan, et al.
Building Simulation (2024) Vol. 17, Iss. 5, pp. 695-722
Closed Access | Times Cited: 7
Correlating the urban microclimate and energy demands in hot climate Contexts: A hybrid review
Nourhan M. Waly, Hamdy Hassan, Ryo MURATA, et al.
Energy and Buildings (2023) Vol. 295, pp. 113303-113303
Closed Access | Times Cited: 14
Accelerating flow simulations in the built environment by using the fast fluid dynamics initializer
Chi Zhang, Chih‐Yung Wen, Yu-Hsuan Juan, et al.
Building and Environment (2024) Vol. 253, pp. 111274-111274
Closed Access | Times Cited: 5
Empowering smart cities with digital twins of buildings: Applications and implementation considerations of data-driven energy modelling in building management
Mariam Elnour, Ahmad Mohammad Ahmad, Shimaa Basheir Abdelkarim, et al.
Building Services Engineering Research and Technology (2024) Vol. 45, Iss. 4, pp. 475-498
Closed Access | Times Cited: 5
A data decomposition and attention mechanism-based hybrid approach for electricity load forecasting
Hadi Oqaibi, Jatin Bedi
Complex & Intelligent Systems (2024) Vol. 10, Iss. 3, pp. 4103-4118
Open Access | Times Cited: 4
A federated and transfer learning based approach for households load forecasting
Gurjot Singh, Jatin Bedi
Knowledge-Based Systems (2024) Vol. 299, pp. 111967-111967
Closed Access | Times Cited: 4
A hybrid model of machine learning for classifying household water-consumption behaviors
Miao Wang, Zonghan Li, Yi Liu, et al.
Cleaner and Responsible Consumption (2025) Vol. 16, pp. 100252-100252
Open Access
Storage economy and markets
Edisson Villa‐Ávila, Paúl Arévalo, Danny Ochoa-Correa, et al.
Elsevier eBooks (2025), pp. 187-209
Closed Access
A state-of-the-art comparative review of load forecasting methods: Characteristics, perspectives, and applications
Mahmudul Hasan, Zannatul Mifta, Sumaiya Janefar Papiya, et al.
Energy Conversion and Management X (2025), pp. 100922-100922
Open Access
MAS-DR: An ML-Based Aggregation and Segmentation Framework for Residential Consumption Users to Assist DR Programs
Petros Tzallas, Alexios Papaioannou, Asimina Dimara, et al.
Sustainability (2025) Vol. 17, Iss. 4, pp. 1551-1551
Open Access
Superblock Typologies: Classification Based on the Parameters of ‘Built Density’, ‘Urban Geometry’ and ‘Street Network’
Najeeba Kutty, Martin Scoppa
Advances in Science, Technology & Innovation/Advances in science, technology & innovation (2025), pp. 159-168
Closed Access
A Thematic Review of AI and ML in Sustainable Energy Policies for Developing Nations
Hassan Qudrat‐Ullah
Energies (2025) Vol. 18, Iss. 9, pp. 2239-2239
Open Access
Machine learning prediction of heating and cooling loads based on Athenian residential buildings’ simulation dataset
Lei Zhang, Mengying Cao, Ning Li, et al.
Energy and Buildings (2025), pp. 115808-115808
Closed Access
Methods and attributes for customer-centric dynamic electricity tariff design: A review
Tasmeea Rahman, Mohammad Lutfi Othman, Samsul Bahari Mohd Noor, et al.
Renewable and Sustainable Energy Reviews (2023) Vol. 192, pp. 114228-114228
Closed Access | Times Cited: 9
Toward Improved Urban Building Energy Modeling Using a Place-Based Approach
Guglielmina Mutani, Pamela Vocale, Kavan Javanroodi
Energies (2023) Vol. 16, Iss. 9, pp. 3944-3944
Open Access | Times Cited: 8
Intrinsically interpretable machine learning-based building energy load prediction method with high accuracy and strong interpretability
Chaobo Zhang, Pieter-Jan Hoes, Shuwei Wang, et al.
Energy and Built Environment (2024)
Open Access | Times Cited: 2
Data-Driven Modelling for Assessing Trophic Status in Marine Ecosystems Using Machine Learning Approaches
Md Galal Uddin, Stephen Nash, Azizur Rahman, et al.
(2023)
Open Access | Times Cited: 4
A Contiguous Temporal Chebyshev Convolutional Optimized Network (CoC-TemNet) Model for Energy Prediction in IoT Enabled Smart City Networks
K. Priyadarsini, Karthik Sekhar, Praveen Kumar Sekhar
IEEE Internet of Things Journal (2024) Vol. 11, Iss. 13, pp. 23630-23643
Closed Access | Times Cited: 1
Navigating the landscape of energy governance: A bibliometric analysis of research trends and future directions
Hossein Tabrizian, Babak Amiri, Mahdi Abdolhamid
Energy Reports (2024) Vol. 12, pp. 2653-2675
Open Access | Times Cited: 1
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