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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:

Surrogate modelling for sustainable building design – A review
Paul Westermann, Ralph Evins
Energy and Buildings (2019) Vol. 198, pp. 170-186
Closed Access | Times Cited: 223

Showing 1-25 of 223 citing articles:

A novel improved model for building energy consumption prediction based on model integration
Ran Wang, Shilei Lu, Wei Feng
Applied Energy (2020) Vol. 262, pp. 114561-114561
Open Access | Times Cited: 182
Recent advances and applications of surrogate models for finite element method computations: a review
Jakub Kůdela, Radomil Matoušek
Soft Computing (2022) Vol. 26, Iss. 24, pp. 13709-13733
Closed Access | Times Cited: 147
Artificial intelligence applied to conceptual design. A review of its use in architecture
Luz Castro, Adrián Carballal, Nereida Rodríguez-Fernández, et al.
Automation in Construction (2021) Vol. 124, pp. 103550-103550
Open Access | Times Cited: 127
Multi-objective optimization of energy performance for a detached residential building with a sunspace using the NSGA-II genetic algorithm
Ana Vukadinović, Jasmina Radosavljević, Amelija Đorđević, et al.
Solar Energy (2021) Vol. 224, pp. 1426-1444
Closed Access | Times Cited: 115
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
Constructing Neural Network Based Models for Simulating Dynamical Systems
Christian Møldrup Legaard, Thomas Schranz, Gerald Schweiger, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 11, pp. 1-34
Open Access | Times Cited: 71
A global model of hourly space heating and cooling demand at multiple spatial scales
Iain Staffell, Stefan Pfenninger, Nathan Johnson
Nature Energy (2023) Vol. 8, Iss. 12, pp. 1328-1344
Open Access | Times Cited: 70
Envelope design for low-energy buildings in the tropics: A review
Vallary Gupta, Chirag Deb
Renewable and Sustainable Energy Reviews (2023) Vol. 186, pp. 113650-113650
Open Access | Times Cited: 41
Applications of artificial intelligence for energy efficiency throughout the building lifecycle: An overview
Raheemat O. Yussuf, Omar S. Asfour
Energy and Buildings (2024) Vol. 305, pp. 113903-113903
Closed Access | Times Cited: 40
Developing surrogate models for the early-stage design of residential blocks using graph neural networks
Zhaoji Wu, Mingkai Li, Wenli Liu, et al.
Building Simulation (2025)
Open Access | Times Cited: 1
Performance-informed urban design: training a generalized surrogate model for predicting building energy demand across residential morphologies in Singapore
Jing Zhi Tay, Thomas Wortmann, Frederick Peter Ortner
Journal of Building Performance Simulation (2025), pp. 1-15
Open Access | Times Cited: 1
An efficient metamodel-based method to carry out multi-objective building performance optimizations
Facundo Bre, Nadia D. Román, Vı́ctor D. Fachinotti
Energy and Buildings (2019) Vol. 206, pp. 109576-109576
Closed Access | Times Cited: 98
Implementing data-driven parametric building design with a flexible toolbox
Nathan C. Brown, Violetta Jusiega, Caitlin Mueller
Automation in Construction (2020) Vol. 118, pp. 103252-103252
Open Access | Times Cited: 92
Multi-objective optimization of energy efficiency and thermal comfort in an existing office building using NSGA-II with fitness approximation: A case study
Mohammadamin Ghaderian, Farzad Veysi
Journal of Building Engineering (2021) Vol. 41, pp. 102440-102440
Closed Access | Times Cited: 76
Predictive models for daylight performance of general floorplans based on CNN and GAN: A proof-of-concept study
Qiushi He, Ziwei Li, Wen Gao, et al.
Building and Environment (2021) Vol. 206, pp. 108346-108346
Closed Access | Times Cited: 68
Data-driven building energy modelling – An analysis of the potential for generalisation through interpretable machine learning
Massimiliano Manfren, P.A.B. James, Lamberto Tronchin
Renewable and Sustainable Energy Reviews (2022) Vol. 167, pp. 112686-112686
Open Access | Times Cited: 61
Techno-economic analysis and energy modelling as a key enablers for smart energy services and technologies in buildings
Massimiliano Manfren, Benedetto Nastasi, Lamberto Tronchin, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 150, pp. 111490-111490
Open Access | Times Cited: 57
Building digital twinning: Data, information, and models
Sungmin Yoon
Journal of Building Engineering (2023) Vol. 76, pp. 107021-107021
Open Access | Times Cited: 39
Machine learning as a surrogate to building performance simulation: Predicting energy consumption under different operational settings
Abdulrahim Ali, Raja Jayaraman, Ahmad Mayyas, et al.
Energy and Buildings (2023) Vol. 286, pp. 112940-112940
Closed Access | Times Cited: 35
In situ modeling methodologies in building operation: A review
Sungmin Yoon
Building and Environment (2023) Vol. 230, pp. 109982-109982
Closed Access | Times Cited: 32
Comfort, carbon emissions, and cost of building envelope and photovoltaic arrangement optimization through a two-stage model
Zhan Jin, Wenjing He, Jianxiang Huang
Applied Energy (2023) Vol. 356, pp. 122423-122423
Closed Access | Times Cited: 23
Architectural spatial layout planning using artificial intelligence
Jaechang Ko, Benjamin Ennemoser, Won-Jae Yoo, et al.
Automation in Construction (2023) Vol. 154, pp. 105019-105019
Closed Access | Times Cited: 22
A protocol for developing and evaluating neural network-based surrogate models and its application to building energy prediction
Danlin Hou, Ralph Evins
Renewable and Sustainable Energy Reviews (2024) Vol. 193, pp. 114283-114283
Open Access | Times Cited: 10
Interactive effects of hyperparameter optimization techniques and data characteristics on the performance of machine learning algorithms for building energy metamodeling
Binghui Si, Zhenyu Ni, Jiacheng Xu, et al.
Case Studies in Thermal Engineering (2024) Vol. 55, pp. 104124-104124
Open Access | Times Cited: 10
Application of Data-Driven Surrogate Models in Structural Engineering: A Literature Review
Delbaz Samadian, Imrose B. Muhit, Nashwan Dawood
Archives of Computational Methods in Engineering (2024)
Closed Access | Times Cited: 10
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