Proper analysis of building energy performance requires selecting appropriate models for
handling complicated calculations. Machine learning has recently emerged as a promising …

Early assessment of the energy performance of buildings (EPB) is focused in this study. This
task is carried out by predicting the cooling load (CL) in a residential building. To this end …

The significance of accurate heating load (HL) approximation is the primary motivation of
this research to distinguish the most efficient predictive model among several neural …

Artificial intelligence algorithms have been applied separately or integrally for prediction,
classification or optimization of buildings energy consumption. However, there is a salient …

This study pursues optima modification of heating, ventilating, and air conditioning (HVAC)
systems embedded in residential buildings through predicting heating load (HL) and cooling …

A reliable prediction of sustainable energy consumption is key for designing environmentally
friendly buildings. In this study, three novel hybrid intelligent methods, namely the …

Recent studies have witnessed remarkable merits of metaheuristic algorithms in
optimization problems. Due to the significance of the early analysis of the thermal load in …

Today's energy resources are closer to consumers due to sustainable energy and advanced
technology. To that end, ensuring a precise prediction of energy consumption at the …

The consumption of energy in buildings holds considerable importance within the realm of
overall energy usage. This underscores the critical nature of employing efficient strategies …

Accurate forecast of energy consumption is essential in building energy management.
Owing to the variation of outdoor weather condition among different seasons, year-round …