Application of Extreme Learning Machine in Fault Classification of Power Transformer

Journals Menu

Follow SCIRP

ISSN Print: 2153-1285
ISSN Online: 2153-1293
www.scirp.org/journal/cs
E-mail: cs@scirp.org

Citations h5-index & Ranking*

"Application of Extreme Learning Machine in Fault Classification of Power Transformer"
written by Athikkan Venkatasami, Pitchai Latha,
published by Circuits and Systems, Vol.7 No.10, 2016

has been cited by the following article(s):

[1]	Bearing Fault Diagnosis Based on Extreme Machine Learning Optimized by Differential Evolution
	2020

[2]	Using Neural Network with Random Weights and Mutual Information for Systolic Peaks Classification of PPG Signals
	2020

[3]	Desenvolvimento de metodologia para diagnóstico de falhas incipientes em transformadores de potência utilizando análise de gases e aprendizado de máquina
	2020

[4]	Causes and Countermeasures of Frequent Action of Gas Relay with on-load Tap Switch
	2020

[5]	Wavelet‐based extreme learning machine for distribution grid fault location
	IET Generation …, 2017

[6]	Wavelet-based extreme learning machine for distribution grid fault location
	2017

[1]	Using Neural Network with Random Weights and Mutual Information for Systolic Peaks Classification of PPG Signals Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology, 2020 DOI:10.1145/3397391.3397394

[2]	Bearing Fault Diagnosis Based on Extreme Machine Learning Optimized by Differential Evolution 2020 Asia-Pacific International Symposium on Advanced Reliability and Maintenance Modeling (APARM), 2020 DOI:10.1109/APARM49247.2020.9209484

[3]	Causes and Countermeasures of Frequent Action of Gas Relay with on-load Tap Switch 2020 5th International Conference on Mechanical, Control and Computer Engineering (ICMCCE), 2020 DOI:10.1109/ICMCCE51767.2020.00151

[4]	Using Neural Network with Random Weights and Mutual Information for Systolic Peaks Classification of PPG Signals Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology, 2020 DOI:10.1145/3397391.3397394

[5]	Using Neural Network with Random Weights and Mutual Information for Systolic Peaks Classification of PPG Signals Proceedings of the 2020 10th International Conference on Biomedical Engineering and Technology, 2020 DOI:10.1145/3397391.3397394

[6]	Wavelet-based extreme learning machine for distribution grid fault location IET Generation, Transmission & Distribution, 2017 DOI:10.1049/iet-gtd.2017.0656

Follow SCIRP