Two-Stage Fault Classification Algorithm for Real Fault Data in Transmission Lines

SH Lim, T Kim, KY Lee, KM Song, SG Yoon - IEEE Access, 2024 - ieeexplore.ieee.org
Fault classification in power transmission lines is important in distance relaying for
identifying the accurate phases implicated in the fault occurrence. Generally, the accuracy of …

Improved Fault Classification and Localization in Power Transmission Networks Using VAE-Generated Synthetic Data and Machine Learning Algorithms

MA Khan, B Asad, T Vaimann, A Kallaste… - Machines, 2023 - mdpi.com
The reliable operation of power transmission networks depends on the timely detection and
localization of faults. Fault classification and localization in electricity transmission networks …

Prediction of solid soluble content of green plum based on improved CatBoost

X Zhang, C Zhou, Q Sun, Y Liu, Y Yang, Z Zhuang - Agriculture, 2023 - mdpi.com
Most green plums need to be processed before consumption, and due to personal
subjective factors, manual harvesting and sorting are difficult to achieve using standardized …

Enhancing Fraud Detection in Banking using Advanced Machine Learning Techniques

U Detthamrong, W Chansanam… - … of Economics and …, 2024 - econjournals.net.tr
This study demonstrates the effectiveness of advanced machine learning techniques in
detecting fraudulent activities within the banking industry. We evaluated the performance of …

Impact of pulse parameters of a DC power generator on the microstructural and mechanical properties of sputtered AlN film with In-Situ OES data analysis

WY Zhou, HF Chen, XL Tseng, HH Lo, PJ Wang… - Materials, 2023 - mdpi.com
In the present study, the sputtered aluminum nitride (AlN) films were processed in a reactive
pulsed DC magnetron system. We applied a total of 15 different design of experiments …

[HTML][HTML] Improving Electrical Fault Detection Using Multiple Classifier Systems

J Oliveira, D Passos, D Carvalho, JFV Melo, EG Silva… - Energies, 2024 - mdpi.com
Machine Learning-based fault detection approaches in energy systems have gained
prominence for their superior performance. These automated approaches can assist …

BOHDL model: a robust framework for fault detection and classification in ring/radial distribution systems

G Tiwari, S Saini, Minaxi - Neural Computing and Applications, 2025 - Springer
Distribution systems are constantly at risk of failure due to various factors, including lightning
strikes, equipment aging, human mistakes, and breakdown of power system components …

Timeseries Fault Classification in Power Transmission lines by Non-intrusive Feature Extraction and Selection using Supervisare Machine Learning

R Nawaz, H Albalawi, SBA Bukhari… - IEEE …, 2024 - ieeexplore.ieee.org
This paper presents a supervised machine learning approach using eight popular classifiers
for fault classification in power transmission lines. The classification of faults, indicated by …

Path Loss Model Estimation at Indoor Offices Environment by Using Deep Neural Network and CatBoost for Millimeter Wave 5G Wireless Application

H Zakeri, P Khoddami, G Moradi… - IEEE …, 2024 - ieeexplore.ieee.org
This paper introduces a novel method for estimating the path loss value in indoor scenarios.
It uses a combination of electromagnetic calculation and machine learning. Using …

Hardware In the Loop Protection Scheme of Compensated Transmission Lines with a Unified Power Flow Controller

J Rodríguez-Herrejón, E Reyes-Archundia… - IEEE …, 2024 - ieeexplore.ieee.org
This paper presents a Hardware in the Loop simulation for the detection, classification, and
location of faults in transmission lines with Unified Power Flow Controller compensation …