The surge of machine learning and increasing data accessibility in buildings provide great
opportunities for applying machine learning to building energy system modeling and …

Building energy consumption modeling and forecasting is essential to address buildings
energy efficiency problems and take up current challenges of human comfort, urbanization …

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 …

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 …

This paper aims to provide a systemic review of how indoor sensors influence in managing
optimal energy saving, thermal comfort, visual comfort, and indoor air quality in the built …

In the European Union, the building sector is one of the largest energy consumer with about
40% of the final energy consumption. Reducing consumption is also a sociological …

Air conditioning system is extensively used in large commercial buildings. The fast and
accurate building cooling load forecasting is the basis for improving the operation efficiency …

The energy performance of buildings was estimated using various data mining techniques,
including support vector regression (SVR), artificial neural network (ANN), classification and …

Commercial office buildings represent the largest in floor area in most developed countries
and utilize substantial amount of energy in the provision of building services to satisfy …

Three main groups of internal and external influencing factors have been identified through
this review, including building characteristics, equipment and technologies, and occupant's …