Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems

Hybrid Deep Learning Approach for Accurate Detection and Multiclass Classification of Broken Conductor Faults in Power Distribution Systems

The identification and classification of broken conductor faults in power distribution systems (PDSs) is challenging because of the nonlinear and complex nature of the unbalanced three-phase currents. Previous approaches to identifying faults fail to resolve the issue of precise fault identification...

Full description

Saved in:
Bibliographic Details
Main Authors: Firas Saadoon Mohammed Al-Jumaili, Mustafa Onat
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Power distribution system
complex value neural networks
long short-term memory
support vector machine
decision tree
random forest
Online Access:https://ieeexplore.ieee.org/document/10788708/
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

https://ieeexplore.ieee.org/document/10788708/

Similar Items