The rapid development of technology in the electrical energy sector within the last 20 years
has led to growing electric power needs through the increased number of electrical …

A data-driven methodology to improve the energy disaggregation accuracy during Non-
Intrusive Load Monitoring is proposed. In detail, the method uses a two-stage classification …

Deep learning methods can recognize the various underwater acoustic targets in complex
marine environments. In this study, we apply deep learning methods in decision recognition …

Non-Intrusive Load Monitoring aims to extract the energy consumption of individual
electrical appliances through disaggregation of the total power consumption as measured …

Non-Intrusive Load Monitoring aims to extract the energy consumption of individual
electrical appliances through disaggregation of the total power consumption as measured …

Smart meters are used to measure the energy consumption of households. Specifically,
within the energy consumption task, a smart meter must be used for load forecasting, the …

Estimation of vehicle components' temperatures is essential to compute their thermal fatigue
and life expectancy, and is typically based on lumped-parameter models, such as thermal …

In this article, the topic of time series modelling is discussed. It highlights the criticality of
analysing and forecasting time series data across various sectors, identifying five primary …

In real-world scenarios, the performance of rolling bearings can be significantly affected by
frequent environmental disturbances, including high-energy fluctuations, transient noises …

The rapid development of technology in the electrical sector within the last 20 years has led
to growing electric power needs through the increased number of electrical appliances and …