Machine learning-based prediction of thermal comfort: exploring building types, climate, ventilation strategies, and seasonal variations

Ali Berkay Avcı

Building Research and Information2025https://doi.org/10.1080/09613218.2025.2462932article
AJG 2ABDC A
Weight
0.60

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14 citations

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https://doi.org/https://doi.org/10.1080/09613218.2025.2462932

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@article{ali2025,
  title        = {{Machine learning-based prediction of thermal comfort: exploring building types, climate, ventilation strategies, and seasonal variations}},
  author       = {Ali Berkay Avcı},
  journal      = {Building Research and Information},
  year         = {2025},
  doi          = {https://doi.org/https://doi.org/10.1080/09613218.2025.2462932},
}

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Machine learning-based prediction of thermal comfort: exploring building types, climate, ventilation strategies, and seasonal variations

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Evidence weight

0.60

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.62 × 0.4 = 0.25
M · momentum0.85 × 0.15 = 0.13
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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