This paper aims to introduce deep learning to the power quality community by reviewing the
latest applications and discussing the open challenges of this technology. Publications …

The rising integration of offshore wind energy into the electric grid provides remarkable
opportunities in terms of environmental sustainability and cost efficiency. However, it poses …

In this paper, a hybrid system is proposed to predict and classifies the power system
transmission line faults. The proposed technique is the consolidation of both the truncated …

Smart healthcare monitoring systems are proliferating due to the Internet of Things (IoT)-
enabled portable medical devices. The IoT and deep learning in the healthcare sector …

This paper offers a systematic literature review of real-time detection and classification of
Power Quality Disturbances (PQDs). A particular focus is given to voltage sags and notches …

The rapid development in deep learning models provide considerable advancements in
emotion recognition by electroencephalogram (EEG). However, existing approaches …

Prognostics and health management (PHM) of turbine cutting tools, particularly the
remaining useful life (RUL) prediction is a Gordian technique to maintain the reliability and …

Artificial intelligence (AI) approaches are usually coupled with the wavelet transform (WT) for
feature extraction to classify the power quality disturbances (PQDs). Therefore, selecting a …

Glaucoma, diabetic retinopathy, diabetic hypertension (DHR), Cataract, and age-related
macular degeneration are some of the most common and important retinal diseases. A …

Several factors affect existing electric power systems and negatively impact power quality
(PQ): the high penetration of renewable and distributed sources that are based on power …