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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 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: 83

Showing 1-25 of 83 citing articles:

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: 73
Physics-informed neural networks for building thermal modeling and demand response control
Yongbao Chen, Qiguo Yang, Zhe Chen, et al.
Building and Environment (2023) Vol. 234, pp. 110149-110149
Closed Access | Times Cited: 40
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: 38
Physics-informed neural nets for control of dynamical systems
Eric Aislan Antonelo, Eduardo Camponogara, Laio Oriel Seman, et al.
Neurocomputing (2024) Vol. 579, pp. 127419-127419
Closed Access | Times Cited: 28
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
Energy flexibility quantification of a tropical net-zero office building using physically consistent neural network-based model predictive control
Wei Liang, Han Li, Sicheng Zhan, et al.
Advances in Applied Energy (2024) Vol. 14, pp. 100167-100167
Open Access | Times Cited: 12
Load Margin Assessment of Power Systems Using Physics-Informed Neural Network with Optimized Parameters
Murilo E. C. Bento
Energies (2024) Vol. 17, Iss. 7, pp. 1562-1562
Open Access | Times Cited: 7
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
An AI framework integrating physics-informed neural network with predictive control for energy-efficient food production in the built environment
Guoqing Hu, Fengqi You
Applied Energy (2023) Vol. 348, pp. 121450-121450
Open Access | Times Cited: 20
Towards scalable physically consistent neural networks: An application to data-driven multi-zone thermal building models
Loris Di Natale, Bratislav Svetozarevic, Philipp Heer, et al.
Applied Energy (2023) Vol. 340, pp. 121071-121071
Open Access | Times Cited: 18
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
Intelligent Approaches to Fault Detection and Diagnosis in District Heating: Current Trends, Challenges, and Opportunities
Jonne van Dreven, Veselka Boeva, Shahrooz Abghari, et al.
Electronics (2023) Vol. 12, Iss. 6, pp. 1448-1448
Open Access | Times Cited: 17
Toward Physics-Informed Machine-Learning-Based Predictive Maintenance for Power Converters—A Review
Youssof Fassi, Vincent Heiries, J. Boutet, et al.
IEEE Transactions on Power Electronics (2023) Vol. 39, Iss. 2, pp. 2692-2720
Closed Access | Times Cited: 17
Demand response for residential building heating: Effective Monte Carlo Tree Search control based on physics-informed neural networks
Fabio Pavirani, Gargya Gokhale, Bert Claessens, et al.
Energy and Buildings (2024) Vol. 311, pp. 114161-114161
Open Access | Times Cited: 6
Physics-constrained graph modeling for building thermal dynamics
Ziyao Yang, Amol D. Gaidhane, Ján Drgoňa, et al.
Energy and AI (2024) Vol. 16, pp. 100346-100346
Open Access | Times Cited: 5
A learning-based model predictive control method for unlocking the potential of building energy flexibility
Jie Zhu, Jide Niu, Sicheng Zhan, et al.
Energy and Buildings (2025), pp. 115299-115299
Closed Access
Complex coupling representation in low-dimensional space for control-oriented energy-consuming industries modeling
J. X. Mu, Chunjie Yang, Yan Feng, et al.
Applied Energy (2025) Vol. 383, pp. 125263-125263
Closed Access
Transfer learning in building dynamics prediction
Gaurav Chaudhary, Hicham Johra, Laurent Georges, et al.
Energy and Buildings (2025), pp. 115384-115384
Open Access
Toward scalable prediction of indoor thermal dynamics: Neural-network-implanted state-space (NNiSS) model
Jeeye Mun, Hyeong-Gon Jo, Cheol Soo Park
Energy and Buildings (2025), pp. 115359-115359
Closed Access
Perspectives for artificial intelligence in sustainable energy systems
Dongyu Chen, Xiaojie Lin, Yiyuan Qiao
Energy (2025), pp. 134711-134711
Closed Access
Data-Driven and Physically Informed Power Grid Dispatch Decision-Making Method
Kai Sun, Dahai Zhang, Jiye Wang, et al.
Sustainable Energy Grids and Networks (2025), pp. 101644-101644
Closed 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
Sensitivity Analysis of Physical Regularization in Physics-informed Neural Networks (PINNs) of Building Thermal Modeling
Yongbao Chen, Huilong Wang, Zhe Chen
Building and Environment (2025), pp. 112693-112693
Closed Access
Physics-informed explainable encoder-decoder deep learning for predictive estimation of building carbon emissions
Chao Chen, Limao Zhang, Cheng Zhou, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 213, pp. 115478-115478
Closed Access
Accuracy, generalizability, and extrapolation ability of physics-based, data-driven, and hybrid models for real-life cooling towers
Jin‐Hong Kim, Young Sub Kim, Hyunji Jo, et al.
Building and Environment (2025), pp. 112756-112756
Closed Access
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