Comparison of the performance of artificial neural networks and fuzzy logic for recognizing different partial discharge sources
This paper compared the capabilities of the artificial neural network (ANN) and the fuzzy logic (FL) approaches for recognizing and discriminating partial discharge (PD) fault classes. The training and testing parameters for the ANN and FL comprise statistical fingerprints from different phase-Ampli...
Saved in:
Main Author: | Bani, N. A. |
---|---|
Format: | Article |
Language: | English |
Published: |
MDPI AG
2017
|
Subjects: | |
Online Access: | http://eprints.utm.my/id/eprint/77115/1/NurulAiniBani2017_ComparisonofthePerformanceofArtificial.pdf http://eprints.utm.my/id/eprint/77115/ https://www.scopus.com/inward/record.uri?eid=2-s2.0-85029061428&doi=10.3390%2fen10071060&partnerID=40&md5=87b8a80ff251313b38333f4bdd774dea |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
Comparison of artificial neural network and multiple regression for partial discharge sources recognition
by: Abubakar Masud A., et al.
Published: (2023) -
Measurement Of Artificial Partial Discharge Sources
by: Muhamad Azlan Bin Awang Yah
Published: (2023) -
Foundations of fuzzy logic and artificial neural networks
by: Abdullah, Shahrum Shah, et al.
Published: (2008) -
Artificial neural network application for partial discharge recognition: survey and future directions
by: Mas'ud, A. A., et al.
Published: (2016) -
Artificial generation of partial discharge sources through an algorithm based on deep convolutional generative adversarial networks
by: Ardila Rey, J. A., et al.
Published: (2020)