Building energy efficiency is important because buildings consume a significant energy
amount. The study proposed additive artificial neural networks (AANNs) for predicting …

The development of a reliable energy use prediction model is still difficult due to the inherent
complex pattern of energy use data. There are few studies developing a prediction model for …

As a popular data driven method, artificial neural networks (ANNs) have been widely
applied in building energy prediction field for decades. To improve the short term prediction …

The forecasting of building energy consumption remains a challenging task because of the
intricate management of the relevant parameters that can influence the performance of …

Building Energy prediction has emerged as an active research area due to its potential in
improving energy efficiency in building energy management systems. Essentially, building …

Recently, the forecasting of energy consumption has prompted a massive escalation in
research studies that are being conducted all over the world in an effort to attain higher …

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

Energy uncertainty and ecological pressures have contributed to a high volatility in energy
demand and consumption. The building sector accounts for 30 to 40% of the total global …

Accurate building energy consumption prediction is crucial to the rational planning of
building energy systems. The energy consumption of buildings is influenced by various …

During the past century, energy consumption and associated greenhouse gas emissions
have increased drastically due to a wide variety of factors including both technological and …