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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:

Analysis of Variables Affecting Indoor Thermal Comfort in Mediterranean Climates Using Machine Learning
Pablo Aparicio-Ruiz, Elena Barbadilla-Martín, José Guadix Martín, et al.
Buildings (2023) Vol. 13, Iss. 9, pp. 2215-2215
Open Access | Times Cited: 13

Showing 13 citing articles:

Enhancing Air Conditioning System Efficiency Through Load Prediction and Deep Reinforcement Learning: A Case Study of Ground Source Heat Pumps
Zhitao Wang, Yubin Qiu, Shiyu Zhou, et al.
Energies (2025) Vol. 18, Iss. 1, pp. 199-199
Open Access | Times Cited: 1
Advancing personal thermal comfort prediction: A data-driven framework integrating environmental and occupant dynamics using machine learning
Maedeh Haghirad, Shahin Heidari, Hojat Hosseini
Building and Environment (2024) Vol. 262, pp. 111799-111799
Closed Access | Times Cited: 9
Preliminary Research on Outdoor Thermal Comfort Evaluation in Severe Cold Regions by Machine Learning
Tianyu Xi, Ming Wang, Enjia Cao, et al.
Buildings (2024) Vol. 14, Iss. 1, pp. 284-284
Open Access | Times Cited: 7
A Comparative Analysis of Machine Learning Algorithms in Predicting the Performance of a Combined Radiant Floor and Fan Coil Cooling System
Shengze Lu, Mengying Cui, Bo Gao, et al.
Buildings (2024) Vol. 14, Iss. 6, pp. 1659-1659
Open Access | Times Cited: 6
Machine Learning Approach for Predicting Personal Thermal Comfort in Air Conditioning Offices in Malaysia
Noor Alam, Sheikh Ahmad Zaki, Syafiq Asyraff Ahmad, et al.
Building and Environment (2024), pp. 112083-112083
Closed Access | Times Cited: 6
Machine learning-based prediction of thermal comfort: exploring building types, climate, ventilation strategies, and seasonal variations
Ali Berkay Avcı
Building Research & Information (2025), pp. 1-18
Closed Access
Assessment and prediction of pedestrian thermal comfort through machine learning modelling in tropical urban climate of Nagpur City
Shivanjali Mohite, Meenal Surawar
Theoretical and Applied Climatology (2024) Vol. 155, Iss. 6, pp. 5607-5628
Closed Access | Times Cited: 2
Methodology to Select Machine Learning Algorithms in Occupant-Centred Control Studies
Thayane Lodete Bilésimo, Luiz Antonio Buschetto Macarini, Diego Antônio Custódio, et al.
(2024)
Closed Access
Living in Mediterranean cities in the context of climate change: A review
P. T. Nastos, Hadas Saaroni
International Journal of Climatology (2024) Vol. 44, Iss. 10, pp. 3169-3190
Open Access
Evaluation of CO 2 and TVOC concentration in a school in Palma during the month of June
Maria-Angels Llabrés-Morey, Susana Hormigos-Jiménez, Mercedes del Río Merino
Building Research & Information (2024), pp. 1-25
Closed Access
A Machine Learning Framework for Optimising Indoor Thermal Comfort and Air Quality through Sensor Data Streams
Chun Wai Chiu, Christos Efstratiou, Marialena Nikolopoulou, et al.
(2024), pp. 329-332
Open Access
Critical insights into thermal comfort optimization and heat resilience in indoor spaces
Harshita Jain
City and Built Environment (2024) Vol. 2, Iss. 1
Open Access
Numerical study of engine room air ventilation systems for landing ship tank class warships in supporting crew comfort and safety
Anton Priyo Nugroho, Wawan Aries Widodo, Is Bunyamin Suryo
IOP Conference Series Earth and Environmental Science (2024) Vol. 1423, Iss. 1, pp. 012004-012004
Open Access
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