The high proportion of energy consumed in buildings has engendered the manifestation of
many environmental problems which deploy adverse impacts on the existence of mankind …

Worldwide, buildings consume a large amount of energy, and a significant share of this
energy is wasted due to system degradation, inappropriate control systems and improper …

Occupant behaviour has significant impacts on the performance of machine learning
algorithms when predicting building energy consumption. Due to a variety of reasons (eg …

Building energy management systems (BEMS) have somewhat standardised building
energy consumption data formats, thereby enhancing their compatibility with the relevant ML …

The feasibility and usefulness of frequency domain fusion of data from multiple vibration
sensors installed on typical industrial rotating machines, based on coherent composite …

Due to their capacity to improve energy consumption performance, intelligent applications
have recently assumed a pivotal position in the energy management of public buildings …

Fault detection and diagnosis (FDD) approaches comprise three main pillars: model-based,
knowledge-based, and data-driven strategies. Data-driven approaches prioritise operational …

The railway-rolling stock wheel flange lubricator protects the wheels and railhead by
lubricating their contacts. Failed or missing flange lubricators can lead to excessive wheel …

Los edificios son uno de los principales actores contaminantes del medio ambiente, por lo
que es necesario fortalecer las estrategias para la reducción de su consumo energético …

Predicting sudden changes in energy consumption within a short time period remains a
challenging task for long-term building energy consumption Prediction. In order to better …