Smart buildings play a crucial role toward decarbonizing society, as globally buildings emit
about one-third of greenhouse gases. In the last few years, machine learning has achieved …

The industrial sector consumes about one-third of global energy, making them a frequent
target for energy use reduction. Variation in energy usage is observed with weather …

Energy is the lifeblood of modern societies. In the past decades, the world's energy
consumption and associated CO 2 emissions increased rapidly due to the increases in …

In the last few years, the application of Model Predictive Control (MPC) for energy
management in buildings has received significant attention from the research community …

A recent surge of interest in building energy consumption has generated a tremendous
amount of energy data, which boosts the data-driven algorithms for broad application …

Ever growing population and progressive municipal business demands for constructing new
buildings are known as the foremost contributor to greenhouse gasses. Therefore …

To meet energy-reduction goals, cities are challenged with assessing building energy
performance and prioritizing efficiency upgrades across existing buildings. Although current …

With the advent of the era of big data, buildings have become not only energy-intensive but
also data-intensive. Data mining technologies have been widely utilized to release the …

Different ways to evaluate the building energy balance can be found in literature, including
comprehensive techniques, statistical and machine-learning methods and hybrid …

The efficient and accurate prediction of building energy consumption can improve the
management of power systems. In this paper, the rough set theory was used to reduce the …