Buildings consume a significant amount of energy throughout their lifecycle; Thus,
sustainable energy management is crucial for all buildings, and controlling energy …

The depletion of fossil fuels and climate change pose huge challenges to sustainable
development. How to meet the increasing energy demands in an efficient and …

Accurate predictions of photovoltaic power generation (PV power) are essential for the
integration of renewable energy into grids, markets, and building energy management …

The task of building energy prediction (BEP) is essential to several emerging research
domains, including energy management, control optimization and fault detection. An …

At present, data-driven methods have achieved satisfactory results in building energy
consumption prediction, especially deep learning models such as long short-term memory …

Traditional building energy prediction (BEP) methods usually solve time-series prediction
problems using either recursive strategy or direct strategy, which may ignore time …

In predicting building energy (affected by seasons), there are issues like inefficient
hyperparameter optimization and inaccurate predictions, it is unclear whether spatial and …

Abstract The European Union's Energy Performance in Buildings Directive has made
significant strides in enhancing building energy efficiency since its inception in 2002 …

The conventional multi-step ahead solar radiation prediction method ignores the time-
dependence of a future solar radiation time series. Therefore, according to sequence-to …

Abstract Machine learning models have seen widespread application in predicting building
thermal loads. Yet, these existing models generally predict the thermal load for a single …