AWARE uses waveform signatures to detect and classify early-stage grid faults, enabling proactive intervention. The system combines physics-based models with AI/ML to interpret subtle electrical ...

According to the analysis, deep learning architectures such as Long Short-Term Memory (LSTM) networks and hybrid CNN-LSTM models deliver more accurate solar radiation and energy output forecasts than ...

A group of researchers led by the University of Sharjah in the UAE proposed to use the convolutional neural network (CNN) technique to detect temperature and shading-induced faults in PV modules. CNN ...

IC manufacturers are increasingly relying on intelligent data processing to prevent downtime, improve yields, and reduce scrap. They are integrating that with fault detection and classification (FDC) ...