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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.

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Showing 1-25 of 176 citing articles:

Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
ACM Computing Surveys (2022) Vol. 55, Iss. 2, pp. 1-96
Open Access | Times Cited: 470
Machine learning applications in urban building energy performance forecasting: A systematic review
Soheil Fathi, Ravi Srinivasan, Andriel Evandro Fenner, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 133, pp. 110287-110287
Closed Access | Times Cited: 231
Review of urban building energy modeling (UBEM) approaches, methods and tools using qualitative and quantitative analysis
Usman Ali, Mohammad Haris Shamsi, Cathal Hoare, et al.
Energy and Buildings (2021) Vol. 246, pp. 111073-111073
Open Access | Times Cited: 195
From concept to application: A review of use cases in urban building energy modeling
Yu Qian Ang, Zachary Berzolla, Christoph Reinhart
Applied Energy (2020) Vol. 279, pp. 115738-115738
Open Access | Times Cited: 184
Tackling Climate Change with Machine Learning
David Rolnick, Priya L. Donti, Lynn H. Kaack, et al.
arXiv (Cornell University) (2019)
Closed Access | Times Cited: 165
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Isaac Kofi Nti, Adebayo Felix Adekoya, Benjamin Asubam Weyori, et al.
Journal of Intelligent Manufacturing (2021) Vol. 33, Iss. 6, pp. 1581-1601
Closed Access | Times Cited: 143
Scenario-based prediction of climate change impacts on building cooling energy consumption with explainable artificial intelligence
Debaditya Chakraborty, Arafat Alam, Saptarshi Chaudhuri, et al.
Applied Energy (2021) Vol. 291, pp. 116807-116807
Closed Access | Times Cited: 117
Machine learning for spatial analyses in urban areas: a scoping review
Ylenia Casali, Nazli Yonca Aydin, Tina Comes
Sustainable Cities and Society (2022) Vol. 85, pp. 104050-104050
Open Access | Times Cited: 91
Accelerated environmental performance-driven urban design with generative adversarial network
Chenyu Huang, Gengjia Zhang, Jiawei Yao, et al.
Building and Environment (2022) Vol. 224, pp. 109575-109575
Closed Access | Times Cited: 85
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: 70
Predicting solar radiation in the urban area: A data-driven analysis for sustainable city planning using artificial neural networking
Alireza Attarhay Tehrani, Omid Veisi, Bahereh Vojdani Fakhr, et al.
Sustainable Cities and Society (2023) Vol. 100, pp. 105042-105042
Closed Access | Times Cited: 47
Urban energy use modeling methods and tools: A review and an outlook
Narjes Abbasabadi, Mehdi Ashayeri
Building and Environment (2019) Vol. 161, pp. 106270-106270
Closed Access | Times Cited: 144
A data-driven approach for multi-scale GIS-based building energy modeling for analysis, planning and support decision making
Usman Ali, Mohammad Haris Shamsi, Mark Bohacek, et al.
Applied Energy (2020) Vol. 279, pp. 115834-115834
Open Access | Times Cited: 123
Machine learning for geographically differentiated climate change mitigation in urban areas
Nikola Milojevic-Dupont, Felix Creutzig
Sustainable Cities and Society (2020) Vol. 64, pp. 102526-102526
Closed Access | Times Cited: 118
Energy prediction techniques for large-scale buildings towards a sustainable built environment: A review
Abdo Abdullah Ahmed Gassar, Seung Hyun
Energy and Buildings (2020) Vol. 224, pp. 110238-110238
Closed Access | Times Cited: 117
A data-driven approach to optimize urban scale energy retrofit decisions for residential buildings
Usman Ali, Mohammad Haris Shamsi, Mark Bohacek, et al.
Applied Energy (2020) Vol. 267, pp. 114861-114861
Open Access | Times Cited: 110
Urban form and building energy use: A systematic review of measures, mechanisms, and methodologies
Steven Jige Quan, Chaosu Li
Renewable and Sustainable Energy Reviews (2021) Vol. 139, pp. 110662-110662
Closed Access | Times Cited: 93
A deep residual neural network identification method for uneven dust accumulation on photovoltaic (PV) panels
Siyuan Fan, Yu Wang, Shengxian Cao, et al.
Energy (2021) Vol. 239, pp. 122302-122302
Closed Access | Times Cited: 93
Developing a common approach for classifying building stock energy models
Jared Langevin, Janet Reyna, Shima Ebrahimigharehbaghi, et al.
Renewable and Sustainable Energy Reviews (2020) Vol. 133, pp. 110276-110276
Open Access | Times Cited: 85
SynCity: Using open data to create a synthetic city of hourly building energy estimates by integrating data-driven and physics-based methods
Jonathan Roth, Amory Martin, Clayton Miller, et al.
Applied Energy (2020) Vol. 280, pp. 115981-115981
Closed Access | Times Cited: 82
Energy Consumption Prediction Using Machine Learning; A Review
Amir Mosavi, Abdullah Bahmani
(2019)
Open Access | Times Cited: 80
An integrated data-driven framework for urban energy use modeling (UEUM)
Narjes Abbasabadi, Mehdi Ashayeri, Rahman Azari, et al.
Applied Energy (2019) Vol. 253, pp. 113550-113550
Closed Access | Times Cited: 77
UBEM.io: A web-based framework to rapidly generate urban building energy models for carbon reduction technology pathways
Yu Qian Ang, Zachary Berzolla, Samuel Letellier-Duchesne, et al.
Sustainable Cities and Society (2021) Vol. 77, pp. 103534-103534
Closed Access | Times Cited: 74
Times series forecasting for urban building energy consumption based on graph convolutional network
Yuqing Hu, Xiaoyuan Cheng, Suhang Wang, et al.
Applied Energy (2021) Vol. 307, pp. 118231-118231
Open Access | Times Cited: 74
From simulation to data-driven approach: A framework of integrating urban morphology to low-energy urban design
Wei Wang, Ke Liu, Muxing Zhang, et al.
Renewable Energy (2021) Vol. 179, pp. 2016-2035
Closed Access | Times Cited: 64
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