Currently, the high energy consumption of district heating system represents a problem.
Thus, accurate prediction of future heat load is the key to ensure energy saving and improve …

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 energy consumption is heavily dependent on its heating load (HL) and cooling load
(CL). Therefore, an efficient building demand forecast is critical for ensuring energy savings …

Short-term building energy consumption prediction is of great significance to the optimal
operation of building energy systems and conservation. Machine-learning models are …

Residential buildings are a significant source of energy consumption and greenhouse gas
emissions, making it crucial to accurately predict their energy demand for reducing their …

Nowadays, since energy management of buildings contributes to the operation cost, many
efforts are made to optimize the energy consumption of buildings. In addition, the most …

Predicting building energy use is necessary for energy planning, management, and
conservation. It is difficult to achieve accurate prediction results due to the inherent …

Accurate prediction of the return temperature is critical to energy efficiency of the district
heating system (DHS). The support vector machines (SVMs) and artificial neural networks …

The increasing of building energy necessitates reliable energy consumption prediction.
Certain research work is necessary to thoroughly illustrate and compare advantages and …

Heating load prediction plays an important role in supporting the operation of a residential
district energy station. To find out the most suitable prediction algorithm, seven popular …