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