Building cooling load predictions can be used to better understand energy demands and to
improve the energy efficiency of HVAC systems. In this study, GA-SVR and GA-WD-SVR …

At present, the high-energy consumption of heating, ventilating, and air conditioning (HVAC)
systems, which is caused by inefficient operation, is a matter of great concern. An accurate …

Building cooling load prediction is one of the key factors in the success of energy-saving
measures. Many computational models available in the industry today have been developed …

Dynamic cooling and heating load forecasting of heating, ventilation and air conditioning
(HVAC) systems is a basis for optimizing the operation of HVAC systems and can contribute …

The cooling load prediction of heating, ventilating and air-conditioning (HVAC) systems in
office buildings is fundamental work for optimizing the operation of HVAC systems. In this …

Cooling load prediction is important and essential for many building energy efficient
controls, such as morning start control of chiller plant. However, most of the existing methods …

Data-driven approaches are widely applied in predicting the cooling load of buildings.
Among these approaches, modelling the decomposed components of the cooling load can …

This study presents four modeling techniques for the prediction of hourly cooling load in the
building. In addition to the traditional back propagation neural network (BPNN), the radial …

Data-driven models can estimate the buildings' energy consumption using machine learning
algorithms. This approach works based on the correlation between energy consumption and …

It is not feasible to apply the traditional prediction method to predict hourly building cooling
load at the urban energy planning stage because of the limited building information and …