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 …

Buildings are one of the main consumers of energy in cities, which is why a lot of research
has been generated around this problem. Especially, the buildings energy management …

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 …

The Electric Energy Consumption Prediction (EECP) is a complex and important process in
an intelligent energy management system and its importance has been increasing rapidly …

Energy consumption prediction has become an integral part of a smart and sustainable
environment. With future demand forecasts, energy production and distribution can be …

A number of decarbonization scenarios for the energy sector are built on simultaneous
electrification of energy demand, and decarbonization of electricity generation through …

Under the background of global warming and the energy crisis, the Chinese government
has set the goal of carbon peaking and carbon neutralization. With the rapid development of …

The single-valued neutrosophic set (SVNS) is a well-known model for handling uncertain
and indeterminate information. Information measures such as distance measures, similarity …

The building sector contributes significantly to overall energy consumption and carbon
emissions. Improving renewable energy utilization in buildings is of considerable …

Urbanization increases electricity demand due to population growth and economic activity.
To meet consumer's demands at all times, it is necessary to predict the future building …