Accurate prediction of chiller energy consumption is essential for optimizing energy usage
and reducing operational costs in commercial buildings. Traditional predictive methods often …

As an indispensable component of air-conditioning system, the air handling unit (AHU)
always exhibits strong nonlinearity and two-directional dynamics (time-wise and batch-wise …

Over the past decade, the utilization of machine learning (ML) models for recognizing hand
gestures from surface electromyography (sEMG) signals has been in demand for the control …

Recent years have witnessed a surge in the development of intelligent fault diagnosis (IFD)
mostly based on deep learning methods, offering increasingly accurate and autonomous …

Accurate sensor measurements are important to normal operation and energy-saving
control of air-conditioning systems in buildings. However, there is currently a lack of faulty …

Air handling unit (AHU) fault detection and diagnosis (FDD) is essential for indoor
environment regulation and building energy conservation. Traditional data-driven FDD …

This study introduces a novel architecture for electricity price forecasting, comprising four
modules designed for prediction and information fusion. Three modules are dedicated to …

Supervised learning methods demonstrated high classification accuracy for air handling unit
(AHU) automated fault detection and diagnosis (FDD) scenarios with well-shaped training …

The utilization of recycled aggregates in the production of recycled aggregate concrete
(RAC) has resulted in its application and advancement in energy preservation and resource …

Fault diagnosis (FD) is essential for ensuring the reliable operation of chillers and
preventing energy waste. Feature selection (FS) is a critical prerequisite for effective FD …