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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:

Machine-learning-based personal thermal comfort modeling for heat recovery using environmental parameters
Mohammad Hadi Fattahi, Mahkame Sharbatdar
Sustainable Energy Technologies and Assessments (2023) Vol. 57, pp. 103294-103294
Closed Access | Times Cited: 10

Showing 10 citing articles:

Machine learning based thermal comfort prediction in office spaces: Integrating SMOTE and SHAP methods
Yiliang Li, Feng Gao, Jiayue Yu, et al.
Energy and Buildings (2025), pp. 115267-115267
Closed Access
The effects of personal comfort systems on sleep: A systematic review
Xinbo Xu, Hui Zhang, Stefano Schiavon, et al.
Renewable and Sustainable Energy Reviews (2025) Vol. 213, pp. 115474-115474
Closed Access
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
Correlations between Crowd Characteristics and Thermal Comfort in Hospitals: A Case Study of Jiangsu Province Hospital
Huan Zhou, Sheng Wang, Miaohui Li, et al.
ICCREM 2021 (2025), pp. 354-364
Closed Access
Machine learning-based assessment of thermal comfort for the elderly in warm environments: Combining the XGBoost algorithm and human body exergy analysis
Mengyuan He, Hong Liu, Shan Zhou, et al.
International Journal of Thermal Sciences (2024) Vol. 209, pp. 109519-109519
Closed Access | Times Cited: 3
Establishment, interpretation and application of logistic regression models for predicting thermal sensation of elderly people
Guozhong Zheng, Xinru Yue, Wenwen Yi, et al.
Energy and Buildings (2024) Vol. 315, pp. 114318-114318
Closed Access | Times Cited: 2
Built thermal environment with multi-directional asymmetric radiations: An experimental study with real occupants
A Yongga, Nianping Li, Yingdong He, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 69, pp. 103918-103918
Closed Access | Times Cited: 1
Predicting Indoor Personalized Heat Stress Using Wearable Sensors and Data-Driven Models
Kopal Nihar, Rishee K. Jain, So‐Min Cheong
Journal of Building Engineering (2024) Vol. 97, pp. 110761-110761
Closed Access | Times Cited: 1
Predictive monitoring of built thermal environment using limited sensor data: A deep learning-based spatiotemporal method
Yue Li, Zheming Tong, Dane Westerdahl, et al.
Sustainable Energy Technologies and Assessments (2024) Vol. 66, pp. 103823-103823
Closed Access
Interpretable general thermal comfort model based on physiological data from wearable bio sensors: Light Gradient Boosting Machine (LightGBM) and SHapley Additive exPlanations (SHAP)
Hyunsoo Kim, Gaang Lee, Hyeunguk Ahn, et al.
Building and Environment (2024), pp. 112127-112127
Closed Access
Toward Optimal Design of a Factory Air Conditioning System Based on Energy Consumption Prediction
Shuwei Zhu, Siying Lv, Wenping Wang, et al.
Processes (2024) Vol. 12, Iss. 12, pp. 2615-2615
Open Access
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