Artificial intelligence (AI) has emerged as an effective solution to alleviate excessive carbon
emissions in sustainable building projects. Although there are numerous applications of AI …

The use of transfer learning for building's electricity loads prediction has shown great
potential when in practice the available electricity consumption data in local energy …

Currently, although energy conservation related research in buildings is a matter of great
urgency in the context of an ever more serious energy crisis, people seem to pay more …

Abstract The discipline of Non-Intrusive Load Monitoring (NILM) has witnessed a surge in
the application of machine learning and pattern recognition approaches, enabling …

Building energy simulation methods for predicting energy consumption suffer from
limitations, including high costs, time-consuming processes, and significant prediction …

Smart building digital twins represent a significant paradigm shift to optimize building
operations, thereby reducing their substantial energy consumption and emissions through …

Building energy models were widely used in building energy performance analysis and
efficiency improvement, such as building demand response assessment and energy system …

This research paper addresses the calibration of an energy simulation model for a naturally
ventilated hospital building located in Mangalore, Karnataka, India, in a warm, humid …

The urban microclimate is essential for accurate simulation-based urban building energy
modelling (UBEM). However, a high spatial-resolution microclimate can increase the …

Addressing the challenges of scalable and cost-effective energy performance analysis in
mid to high-rise office buildings, this paper introduces a novel approach utilizing an inverse …