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

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 …

Accurate and reliable short-term forecasting of wind power is vital for balancing energy and
integrating wind power into a grid. A novel hybrid deep learning model is designed in this …

Buildings consume about half of the global electrical energy, and an accurate prediction of
their electricity consumption is crucial for building microgrids' efficient and reliable …

Due to global warming and climate changes, buildings including residential and commercial
are significant contributors to energy consumption. To this end, net zero energy building …

The operations of renewable power generation systems highly depend on precise
Photovoltaic (PV) power forecasting, providing significant economic, and environmental …

Within last decade, the investing habits of people is rapidly increasing towards stock market.
The nonlinearity and high volatility of stock prices have made it challenging to predict stock …

Electric load forecasting, especially short-term load forecasting, is of significant importance
for the safe and efficient operation of power grids. With the wide adoption of advanced smart …

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 …

Abstract Human Activity Recognition (HAR) involves the recognition of human activities
using sensor data. Most of the techniques for HAR involve hand-crafted features and hence …