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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:

Physics-informed linear regression is competitive with two Machine Learning methods in residential building MPC
Felix Bünning, Benjamin Huber, Adrian Schalbetter, et al.
Applied Energy (2022) Vol. 310, pp. 118491-118491
Open Access | Times Cited: 69

Showing 1-25 of 69 citing articles:

Physics informed neural networks for control oriented thermal modeling of buildings
Gargya Gokhale, Bert Claessens, Chris Develder
Applied Energy (2022) Vol. 314, pp. 118852-118852
Open Access | Times Cited: 84
Physically Consistent Neural Networks for building thermal modeling: Theory and analysis
Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, et al.
Applied Energy (2022) Vol. 325, pp. 119806-119806
Open Access | Times Cited: 74
Building thermal modeling and model predictive control with physically consistent deep learning for decarbonization and energy optimization
Tianqi Xiao, Fengqi You
Applied Energy (2023) Vol. 342, pp. 121165-121165
Closed Access | Times Cited: 40
Real-life data-driven model predictive control for building energy systems comparing different machine learning models
Phillip Stoffel, Max Berktold, Dirk Müller
Energy and Buildings (2024) Vol. 305, pp. 113895-113895
Open Access | Times Cited: 18
A comparison between grey-box models and neural networks for indoor air temperature prediction in buildings
Jacopo Vivian, Enrico Prataviera, N. Gastaldello, et al.
Journal of Building Engineering (2024) Vol. 84, pp. 108583-108583
Closed Access | Times Cited: 16
Active Physics-Informed Deep Learning: Surrogate Modeling for Nonplanar Wavefront Excitation of Topological Nanophotonic Devices
Fatemeh Davoodi
Nano Letters (2025)
Open Access | Times Cited: 1
Evaluation of advanced control strategies for building energy systems
Phillip Stoffel, Laura Maier, Alexander Kümpel, et al.
Energy and Buildings (2022) Vol. 280, pp. 112709-112709
Open Access | Times Cited: 56
Distributed model predictive control of buildings and energy hubs
Nicolas Lefebure, Mohammad Khosravi, Mathias Hudoba de Badyn, et al.
Energy and Buildings (2022) Vol. 259, pp. 111806-111806
Open Access | Times Cited: 38
Field test of Model Predictive Control in residential buildings for utility cost savings
Dan Wang, Yangzhe Chen, Wei Wang, et al.
Energy and Buildings (2023) Vol. 288, pp. 113026-113026
Closed Access | Times Cited: 32
Electricity peak shaving for commercial buildings using machine learning and vehicle to building (V2B) system
Mahdi Ghafoori, Moatassem Abdallah, Seo Young Kim
Applied Energy (2023) Vol. 340, pp. 121052-121052
Closed Access | Times Cited: 21
Field demonstration of predictive heating control for an all-electric house in a cold climate
Elias N. Pergantis, Priyadarshan Priyadarshan, Nadah Al Theeb, et al.
Applied Energy (2024) Vol. 360, pp. 122820-122820
Open Access | Times Cited: 9
Field experiment testing of a low-cost model predictive controller (MPC) for building heating systems and analysis of phase change material (PCM) integration
Zhichen Wei, John Kaiser Calautit
Applied Energy (2024) Vol. 360, pp. 122750-122750
Open Access | Times Cited: 8
Energy optimization algorithms for multi-residential buildings: A model predictive control application
J.M. Hernandez Cid, Angelos Mylonas, Thibault Péan, et al.
Energy and Buildings (2024) Vol. 319, pp. 114562-114562
Open Access | Times Cited: 8
Hydrogen jet and diffusion modeling by physics-informed graph neural network
Xinqi Zhang, Jihao Shi, Junjie Li, et al.
Renewable and Sustainable Energy Reviews (2024) Vol. 207, pp. 114898-114898
Closed Access | Times Cited: 8
Sharing is caring: An extensive analysis of parameter-based transfer learning for the prediction of building thermal dynamics
Giuseppe Pinto, Riccardo Messina, Han Li, et al.
Energy and Buildings (2022) Vol. 276, pp. 112530-112530
Open Access | Times Cited: 28
Physics-Informed Machine Learning for Modeling and Control of Dynamical Systems
Truong X. Nghiem, Ján Drgoňa, Colin N. Jones, et al.
2022 American Control Conference (ACC) (2023)
Open Access | Times Cited: 21
Adaptive thermal load prediction in residential buildings using artificial neural networks
Mohammad Hossein Fouladfar, A. Soppelsa, Himanshu Nagpal, et al.
Journal of Building Engineering (2023) Vol. 77, pp. 107464-107464
Open Access | Times Cited: 20
Physics-informed hierarchical data-driven predictive control for building HVAC systems to achieve energy and health nexus
Xuezheng Wang, Bing Dong
Energy and Buildings (2023) Vol. 291, pp. 113088-113088
Closed Access | Times Cited: 18
Real-time machine-learning-based optimization using Input Convex Long Short-Term Memory network
Z. Y. Wang, Donghan Yu, Zhe Wu
Applied Energy (2024) Vol. 377, pp. 124472-124472
Closed Access | Times Cited: 5
Analyzing the overrated performance of model-based predictive control and energy saving strategies in building energy management: A Review
Abu Talib, Jaewan Joe
Journal of Building Engineering (2025), pp. 111909-111909
Closed Access
Data–model Fusion Methods and Applications toward Smart Manufacturing and Digital Engineering
Fei Tao, Yilin Li, Yupeng Wei, et al.
Engineering (2025)
Open Access
A review on full-, zero-, and partial-knowledge based predictive models for industrial applications
Stefano Zampini, Guido Parodi, Luca Oneto, et al.
Information Fusion (2025), pp. 102996-102996
Open Access
Künstliche Intelligenz in der Bauphysik – Hintergrund, Anwendungen und Potenziale

(2025), pp. 395-434
Closed Access
Real long-term performance evaluation of an improved office building operation involving a Data-driven model predictive control
Peter Klanatsky, François Veynandt, Christian Heschl, et al.
Energy and Buildings (2025), pp. 115590-115590
Open Access
Performance evaluation of deep learning architectures for load and temperature forecasting under dataset size constraints and seasonality
Wonjun Choi, Sangwon Lee
Energy and Buildings (2023) Vol. 288, pp. 113027-113027
Closed Access | Times Cited: 15
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