Review on occupant-centric thermal comfort sensing, predicting, and controlling
Ensuring occupants' thermal comfort and work performance is one of the primary objectives
for building environment conditioning systems. In recent years, there emerged many …
for building environment conditioning systems. In recent years, there emerged many …
Data-driven thermal comfort model via support vector machine algorithms: Insights from ASHRAE RP-884 database
Many models can predict building occupants' thermal comfort, but their accuracies were not
always perfect due to the limited self-learning and self-correction capability when varying the …
always perfect due to the limited self-learning and self-correction capability when varying the …
Data-driven simulation of a thermal comfort-based temperature set-point control with ASHRAE RP884
In the course of thermal comfort theory, researchers have been investigating both static
thermal comfort and adaptive thermal comfort. Compared to static thermal comfort metrics …
thermal comfort and adaptive thermal comfort. Compared to static thermal comfort metrics …
The use of artificial intelligence (AI) methods in the prediction of thermal comfort in buildings: Energy implications of AI-based thermal comfort controls
Buildings consume about 40% of globally-produced energy. A notable amount of this energy
is used to provide sufficient comfort levels to the building occupants. Moreover, given recent …
is used to provide sufficient comfort levels to the building occupants. Moreover, given recent …
A hybrid deep transfer learning strategy for thermal comfort prediction in buildings
Since the thermal condition of living spaces affects the occupants' productivity and their
quality of life, it is important to design effective heating, ventilation and air conditioning …
quality of life, it is important to design effective heating, ventilation and air conditioning …
A feedforward neural network based indoor-climate control framework for thermal comfort and energy saving in buildings
Building air-conditioning and mechanical ventilation (ACMV) systems are responsible for
significant energy consumption and yet, dissatisfaction with the thermal environment is …
significant energy consumption and yet, dissatisfaction with the thermal environment is …
Performance based thermal comfort control (PTCC) using deep reinforcement learning for space cooling
YR Yoon, HJ Moon - Energy and Buildings, 2019 - Elsevier
With the recent increase in energy consumption in buildings, energy-saving strategies in
buildings have become a priority in the energy policies of many countries. Therefore, many …
buildings have become a priority in the energy policies of many countries. Therefore, many …
Data-driven personal thermal comfort prediction: A literature review
Personal thermal comfort prediction modeling has become a trending topic in efforts to
improve individual indoor comfort, a notion that is closely related to the design and …
improve individual indoor comfort, a notion that is closely related to the design and …
Application of machine learning in thermal comfort studies: A review of methods, performance and challenges
ZQ Fard, ZS Zomorodian, SS Korsavi - Energy and Buildings, 2022 - Elsevier
This paper provides a systematic review on the application of Machine Learning (ML) in
thermal comfort studies to highlight the latest methods and findings and provide an agenda …
thermal comfort studies to highlight the latest methods and findings and provide an agenda …
DeepComfort: Energy-efficient thermal comfort control in buildings via reinforcement learning
Heating, ventilation, and air conditioning (HVAC) are extremely energy consuming,
accounting for 40% of total building energy consumption. It is crucial to design some energy …
accounting for 40% of total building energy consumption. It is crucial to design some energy …