This review provides a comprehensive overview of the state-of-the-art methods of graph-
based networks from a deep learning perspective. Graph networks provide a generalized …

This paper proposes a new machine learning approach for fault detection and classification
tasks in electrical power transmission networks. This method exploits the temporal sequence …

As part of any Prognostics and Health Management (PHM) system for the shipping industry,
the determination of the current health of marine systems is fundamental. As such …

Timely detection and classification of faults on transmission lines are crucial requirements
for maintaining a reliable power supply to consumers. Rapid fault detection demands the …

The microgrid technology must be conforming in electrical power system to cater the
expanding development in power demand in the present scenario, and it is extremely …

This paper focuses on the detection of faults occurring in electrical power transmission lines
using machine learning techniques and algorithms. In the recent era, the demand for …

Current fiber-optic distributed acoustic sensor (DAS) target recognition technologies
continue to prioritize updating the feature learning tools while neglecting varying …

Power system includes complex dynamic and interacting elements, which yields to electrical
faults. To maintain electrical power system in stable condition identification of fault detection …

This paper introduces a novel architecture for anomaly detection and classification of high-
voltage transmission line using the self-attention convolutional neural network enhanced …

Due to the rapid progress in data-driven computational imaging, hyperspectral image
classification has become the center for attention. Hyperspectral image as a three …