In theory, building automation and management systems (BAMSs) can provide all the
components and functionalities required for analyzing and operating buildings. However, in …

The difficulty in balancing energy supply and demand is increasing due to the growth of
diversified and flexible building energy resources, particularly the rapid development of …

Artificial Intelligence (AI), machine learning (ML), and deep learning (DL) are emerging
techniques capable of delivering elegant and affordable solutions which can surpass those …

In general, reliable PV generation prediction is required to increase complete control quality
and avoid potential damage. Accurate forecasting of direct solar radiation trends in PV …

Smart cities attempt to reach net-zero emissions goals by reducing wasted energy while
improving grid stability and meeting service demand. This is possible by adopting next …

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 …

Building energy prediction plays a vital role in developing a model predictive controller for
consumers and optimizing energy distribution plan for utilities. Common approaches for …

Data driven building energy consumption forecasting models play a significant role in
enhancing the energy efficiency of the buildings through building energy management …

While unavoidable, inspections, progress monitoring, and comparing as-planned with as-
built conditions in construction projects do not readily add tangible intrinsic value to the end …

This paper presents a new, multi-objective method of analysing and optimising the energy
processes associated with window system design in office buildings. The simultaneous …