Operating points as communication bridge between energy evaluation with air temperature and velocity based on extreme learning machine (ELM) models

This paper aims to evaluate the high energy demand components in the buildings, such as HVAC system, with respect to the indoor environmental parameters, such as ambient air temperature and velocity. The Extreme Learning Machine (ELM) was chosen to be trained from the experimental data in the thermal laboratory due to its accuracy and less computational complexity from many previous researches and studies. Therefore the given physical environmental parameters are able to be predicting the energy consumptions level from the ELM model of Air Handling Unit (AHU) of HVAC systems.