Hyeun Jun Moon
- (2024): A Non-Intrusive Method for Lonely Death Prevention Using Occupancy Detection and an Anomaly Detection Model. Dans: Buildings, v. 14, n. 5 (24 avril 2024).
- (2023): Anomaly Detection Based on LSTM Learning in IoT-Based Dormitory for Indoor Environment Control. Dans: Buildings, v. 13, n. 11 (26 octobre 2023).
- (2023): The Performance of Reinforcement Learning for Indoor Climate Control Devices according to the Level of Outdoor Air Particulate Matters. Dans: Buildings, v. 13, n. 12 (22 novembre 2023).
- A detailed occupant activity classification model in a residential environment using building monitoring data: Considering occupant characteristics. Dans: Energy and Buildings, v. 305 (février 2024). (2024):
- Occupancy estimation using IoT sensors and machine learning: Incorporating ventilation system operating state and preprocessed differential pressure data. Dans: Building and Environment, v. 246 (décembre 2023). (2023):
- A Non-intrusive Data-driven model for detailed Occupants’ activities classification in residential buildings using environmental and energy usage data. Dans: Energy and Buildings, v. 256 (février 2022). (2022):
- An integrated comfort control with cooling, ventilation, and humidification systems for thermal comfort and low energy consumption. Dans: Science and Technology for the Built Environment, v. 23, n. 2 (décembre 2016). (2016):
- Effects of indoor water sounds on intrusive noise perception and speech recognition in rooms. Dans: Building Services Engineering Research and Technology, v. 39, n. 6 (octobre 2018). (2018):
- An interoperability workbench for design analysis integration. Dans: Energy and Buildings, v. 36, n. 8 (août 2004). (2004):
- Determining operation schedules of heat recovery ventilators for optimum energy savings in high-rise residential buildings. Dans: Energy and Buildings, v. 46 (mars 2012). (2012):
- The effect of moisture transportation on energy efficiency and IAQ in residential buildings. Dans: Energy and Buildings, v. 75 (juin 2014). (2014):
- Evaluation of the influence of hygric properties of wallpapers on mould growth rates using hygrothermal simulation. Dans: Energy and Buildings, v. 98 (juillet 2015). (2015):
- Application of a multiple linear regression and an artificial neural network model for the heating performance analysis and hourly prediction of a large-scale ground source heat pump system. Dans: Energy and Buildings, v. 165 (avril 2018). (2018):
- Energy consumption model with energy use factors of tenants in commercial buildings using Gaussian process regression. Dans: Energy and Buildings, v. 168 (juin 2018). (2018):
- Performance based thermal comfort control (PTCC) using deep reinforcement learning for space cooling. Dans: Energy and Buildings, v. 203 (novembre 2019). (2019):
- Combined effects of acoustic, thermal, and illumination conditions on the comfort of discrete senses and overall indoor environment. Dans: Building and Environment, v. 148 (janvier 2019). (2019):
- Cross-modal effects of illuminance and room temperature on indoor environmental perception. Dans: Building and Environment, v. 146 (décembre 2018). (2018):
- Case study of an advanced integrated comfort control algorithm with cooling, ventilation, and humidification systems based on occupancy status. Dans: Building and Environment, v. 133 (avril 2018). (2018):
- Development of an occupancy prediction model using indoor environmental data based on machine learning techniques. Dans: Building and Environment, v. 107 (octobre 2016). (2016):
- Empowerment of decision-makers in mould remediation. Dans: Building Research & Information, v. 36, n. 5 ( 2008). (2008):
- Indoor Air Quality Performance of Ventilation Systems in Classrooms. Dans: Journal of Asian Architecture and Building Engineering, v. 15, n. 2 (mai 2016). (2016):