Open Access
Thermal Environmental Conditions for Human Occupancy
Standard Ashrae
- Vol. 5
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The article was published on 1992-01-01 and is currently open access. It has received 5855 citations till now. The article focuses on the topics: Occupancy.read more
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Machine learning approaches to predict thermal demands using skin temperatures: Steady-state conditions
TL;DR: Considering the overfitting possibility and the cases without learning processes, SVM classifiers with a linear kernel are preferred over Gaussian kernel ones.
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Thermal comfort prediction using normalized skin temperature in a uniform built environment
TL;DR: In this article, a method termed as Predicted Thermal State (PTS) model is presented, which uses the peripheral skin temperature and its gradient features from a single body location to evaluate the thermal state.
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Development of benchmark models for the Egyptian residential buildings sector
TL;DR: In this paper, two building performance simulation models are created reflecting the average energy consumption characteristics of air-conditioned residential apartments in Alexandria, Cairo and Asyut, and the simulation models were verified against the apartment characteristic found in the survey.
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Neural computing thermal comfort index for HVAC systems
TL;DR: In this article, a feed forward neural network model is proposed as an explicit function of the relation of the predicted mean vote (PMV index to accessible variables, i.e. the air temperature, wet bulb temperature, globe temperature, air velocity, clothing insulation and human activity.
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The dynamics of thermal comfort expectations: The problem, challenge and impication
TL;DR: In this article, a comparative questionnaire survey was conducted in China where indoor thermal environments during winter in the northern region (with pervasive district heating) are much warmer than in the southern region (without district heating).