Yang-Seon Kim
- Investigating the Impact of Data Normalization Methods on Predicting Electricity Consumption in a Building Using different Artificial Neural Network Models.. In: Sustainable Cities and Society. :
- Predictions of electricity consumption in a campus building using occupant rates and weather elements with sensitivity analysis: Artificial neural network vs. linear regression. In: Sustainable Cities and Society, v. 62 (November 2020). (2020):
- Impact of correlation of plug load data, occupancy rates and local weather conditions on electricity consumption in a building using four back-propagation neural network models. In: Sustainable Cities and Society, v. 62 (November 2020). (2020):
- Development of a standard capture efficiency test method for residential kitchen ventilation. In: Science and Technology for the Built Environment, v. 24, n. 2 (Januar 2018). (2018):
- Impact of occupancy rates on the building electricity consumption in commercial buildings. In: Energy and Buildings, v. 138 (März 2017). (2017):
- Occupant perceptions and a health outcome in retail stores. In: Building and Environment, v. 93 (November 2015). (2015):