Newer generation sources and loads are posing new challenges to the conventional power
system protection schemes. Adaptive and intelligent protection methodology, based on …

Extreme learning machine (ELM) has gained increasing interest from various research fields
recently. In this review, we aim to report the current state of the theoretical research and …

Protection of high voltage transmission lines is one of the crucial problems in the power
system engineering. Accurate and timely detection and identification of transmission line …

This paper introduces a novel self-attention convolutional neural network (SAT-CNN) model
for detection and classification (FDC) of transmission line faults. The transmission lines …

Recently, a novel learning algorithm for single-hidden-layer feedforward neural networks
(SLFNs) named extreme learning machine (ELM) was proposed by Huang et al. The …

Fault diagnosis for rolling bearings under variable conditions is a hot and relatively difficult
topic, thus an intelligent fault diagnosis method based on local mean decomposition (LMD) …

Fast detection and isolation of faults in a DC microgrid is of particular importance. Fast
trip** protection (i) increases the lifetime of power electronics (PE) switches by avoiding …

This paper investigates support vector machine based fault type and distance estimation
scheme in a long transmission line. The planned technique uses post fault single cycle …

Fault analysis and diagnosis constitute a relevant problem in power systems, with important
economic impacts for operators, maintenance agents and the power industry in general …

Feedforward neural networks (FFNN) have been utilised for various research in machine
learning and they have gained a significantly wide acceptance. However, it was recently …