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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:

Developing surrogate ANN for selecting near-optimal building energy renovation methods considering energy consumption, LCC and LCA
Seyed Amirhosain Sharif, Amin Hammad
Journal of Building Engineering (2019) Vol. 25, pp. 100790-100790
Closed Access | Times Cited: 130

Showing 1-25 of 130 citing articles:

Building information modelling applications in smart buildings: From design to commissioning and beyond A critical review
Christiana Panteli, Angeliki Kylili, Paris A. Fokaides
Journal of Cleaner Production (2020) Vol. 265, pp. 121766-121766
Closed Access | Times Cited: 163
Energy performance optimization of existing buildings: A literature review
Najme Hashempour, Roohollah Taherkhani, Mahdi Mahdikhani
Sustainable Cities and Society (2019) Vol. 54, pp. 101967-101967
Closed Access | Times Cited: 160
Application and characterization of metamodels based on artificial neural networks for building performance simulation: A systematic review
Nadia D. Román, Facundo Bre, Vı́ctor D. Fachinotti, et al.
Energy and Buildings (2020) Vol. 217, pp. 109972-109972
Closed Access | Times Cited: 137
Predicting energy consumption for residential buildings using ANN through parametric modeling
Emad Elbeltagi, Hossam Wefki
Energy Reports (2021) Vol. 7, pp. 2534-2545
Open Access | Times Cited: 105
A review of surrogate-assisted evolutionary algorithms for expensive optimization problems
Chunlin He, Zhang Yon, Dunwei Gong, et al.
Expert Systems with Applications (2023) Vol. 217, pp. 119495-119495
Closed Access | Times Cited: 99
The application of life cycle assessment in buildings: challenges, and directions for future research
Abdulrahman Fnais, Yacine Rezgui, Ioan Petri, et al.
The International Journal of Life Cycle Assessment (2022) Vol. 27, Iss. 5, pp. 627-654
Open Access | Times Cited: 83
Advances in application of machine learning to life cycle assessment: a literature review
Ali Ghoroghi, Yacine Rezgui, Ioan Petri, et al.
The International Journal of Life Cycle Assessment (2022) Vol. 27, Iss. 3, pp. 433-456
Open Access | Times Cited: 81
Buildings' energy consumption prediction models based on buildings’ characteristics: Research trends, taxonomy, and performance measures
Amal A. Al-Shargabi, Abdulbasit Almhafdy, Dina M. Ibrahim, et al.
Journal of Building Engineering (2022) Vol. 54, pp. 104577-104577
Closed Access | Times Cited: 74
Building performance simulation in the brave new world of artificial intelligence and digital twins: A systematic review
Pieter de Wilde
Energy and Buildings (2023) Vol. 292, pp. 113171-113171
Open Access | Times Cited: 69
Metamodel-based simulation optimization: A systematic literature review
João Victor Soares do Amaral, José Arnaldo Barra Montevechi, Rafael de Carvalho Miranda, et al.
Simulation Modelling Practice and Theory (2021) Vol. 114, pp. 102403-102403
Closed Access | Times Cited: 100
Life Cycle Sustainability Assessment in Building Energy Retrofitting; A Review
Hashem Amini Toosi, Monica Lavagna, Fabrizio Leonforte, et al.
Sustainable Cities and Society (2020) Vol. 60, pp. 102248-102248
Closed Access | Times Cited: 95
Practical issues in implementing machine-learning models for building energy efficiency: Moving beyond obstacles
Zeyu Wang, Jian Liu, Yuanxin Zhang, et al.
Renewable and Sustainable Energy Reviews (2021) Vol. 143, pp. 110929-110929
Closed Access | Times Cited: 91
Systematic Review of Deep Learning and Machine Learning for Building Energy
Sina Ardabili, Leila Abdolalizadeh, Csaba Makó, et al.
Frontiers in Energy Research (2022) Vol. 10
Open Access | Times Cited: 63
What is the optimal robust environmental and cost-effective solution for building renovation? Not the usual one
Alina Galimshina, Maliki Moustapha, Alexander Hollberg, et al.
Energy and Buildings (2021) Vol. 251, pp. 111329-111329
Open Access | Times Cited: 60
Bio-based materials as a robust solution for building renovation: A case study
Alina Galimshina, Maliki Moustapha, Alexander Hollberg, et al.
Applied Energy (2022) Vol. 316, pp. 119102-119102
Open Access | Times Cited: 47
Data-driven approach to predicting the energy performance of residential buildings using minimal input data
Ji-Hyun Seo, Seo-Hoon Kim, Sung Lee, et al.
Building and Environment (2022) Vol. 214, pp. 108911-108911
Closed Access | Times Cited: 37
A review of machine learning applications in life cycle assessment studies
Xiaobo Xue Romeiko, Xuesong Zhang, Yulei Pang, et al.
The Science of The Total Environment (2023) Vol. 912, pp. 168969-168969
Open Access | Times Cited: 21
Improving the performance of prefabricated houses through multi-objective optimization design
Yingbo Ji, Junyi Lv, Hong Li, et al.
Journal of Building Engineering (2024) Vol. 84, pp. 108579-108579
Closed Access | Times Cited: 11
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
Strategies for robust renovation of residential buildings in Switzerland
Alina Galimshina, Maliki Moustapha, Alexander Hollberg, et al.
Nature Communications (2024) Vol. 15, Iss. 1
Open Access | Times Cited: 9
Research on green renovations of existing public buildings based on a cloud model –TOPSIS method
Yang Liu, Hongyu Chen, Xian‐Jia Wang
Journal of Building Engineering (2020) Vol. 34, pp. 101930-101930
Closed Access | Times Cited: 63
Artificial neural networks for sustainable development: a critical review
Ivan Henderson V. Gue, Aristotle T. Ubando, Ming‐Lang Tseng, et al.
Clean Technologies and Environmental Policy (2020) Vol. 22, Iss. 7, pp. 1449-1465
Closed Access | Times Cited: 58
The impact of imperfect maintenance actions on the degradation of buildings’ envelope components
Cláudia Ferreira, Ana Silva, Jorge de Brito, et al.
Journal of Building Engineering (2020) Vol. 33, pp. 101571-101571
Closed Access | Times Cited: 53
Statistical method to identify robust building renovation choices for environmental and economic performance
Alina Galimshina, Maliki Moustapha, Alexander Hollberg, et al.
Building and Environment (2020) Vol. 183, pp. 107143-107143
Open Access | Times Cited: 50
Machine Learning Technologies for Sustainability in Smart Cities in the Post-COVID Era
Ana de las Heras, Amalia Luque Sendra, Francisco Zamora‐Polo
Sustainability (2020) Vol. 12, Iss. 22, pp. 9320-9320
Open Access | Times Cited: 50
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