Ahmad Almadhor1, Chitapong Wechtaisong2,*, Usman Tariq3, Natalia Kryvinska4,*, Abdullah Al Hejaili5, Uzma Ghulam Mohammad6, Mohana Alanazi7
Computer Systems Science and Engineering, Vol.48, No.1, pp. 199-216, 2024, DOI:10.32604/csse.2023.039546
- 26 January 2024
Abstract Thermal comfort is an essential component of smart cities that helps to upgrade, analyze, and realize intelligent buildings. It strongly affects human psychological and physiological levels. Residents of buildings suffer stress because of poor thermal comfort. Buildings frequently use Heating, Ventilation, and Air Conditioning (HVAC) systems for temperature control. Better thermal states directly impact people’s productivity and health. This study revealed a human thermal comfort model that makes better predictions of thermal sensation by identifying essential features and employing a tuned Extra Tree classifier, MultiLayer Perceptron (MLP) and Naive Bayes (NB) models. The study employs More >
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