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Arabian Journal for Science and Engineering
Published in: Arabian Journal for Science and Engineering 2/2022

07-09-2021 | Research Article-Computer Engineering and Computer Science

Thermal Comfort Model for HVAC Buildings Using Machine Learning

Authors: Muhammad Fayyaz, Asma Ahmad Farhan, Abdul Rehman Javed

Published in: Arabian Journal for Science and Engineering | Issue 2/2022

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Abstract

Thermal comfort is a condition of mind that expresses satisfaction with the thermal environment. Thermal comfort is critical for both health and productivity. Inadequate thermal comfort results in stress for building inhabitants. Improved thermal conditions are directly related to improved health and productivity of individuals. This paper proposes a novel human thermal comfort model using machine learning algorithms that identify the key features and predict thermal sensation with higher accuracy. We evaluate our approach using tenfold cross-validation and compare our results with state-of-the-art Fanger’s model. Our approach achieves a higher accuracy of 86.08%. Our results demonstrate the potential of our approach to predict thermal sensation votes under wide-ranging thermal conditions correctly.
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Metadata
Title
Thermal Comfort Model for HVAC Buildings Using Machine Learning
Authors
Muhammad Fayyaz
Asma Ahmad Farhan
Abdul Rehman Javed
Publication date
07-09-2021
Publisher
Springer Berlin Heidelberg
Published in
Arabian Journal for Science and Engineering / Issue 2/2022
Print ISSN: 2193-567X
Electronic ISSN: 2191-4281
DOI
https://doi.org/10.1007/s13369-021-06156-8

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