@inproceedings{a51dc9c3b8d64ffd9c41a84d5d7e25ea,
title = "A Deep Learning Based Methodology Development for Fault Classification in Transmission Lines",
abstract = "This work proposes a methodology based on Deep Learning, such as recurrent neural networks (RNN) and long-short-term memory networks (LSTM) to classify faults in transmission lines in power systems. The implemented neural network is trained using data from the measurements of electric currents during the presence of faults that were obtained by simulation. The trained neural network is able to correctly classify faults using the current signature.",
keywords = "Deep learning, Electric Current, LSTM, RNN, Transmission Line",
author = "Daniela Mora and Silvana Gamboa and Alberto Sanchez",
note = "Publisher Copyright: {\textcopyright} 2023 IEEE.; 41st IEEE Central America and Panama Convention, CONCAPAN 2023 ; Conference date: 08-11-2023 Through 10-11-2023",
year = "2023",
doi = "10.1109/CONCAPANXLI59599.2023.10517550",
language = "Ingl{\'e}s",
series = "Proceeding of the 2023 IEEE 41st Central America and Panama Convention, CONCAPAN XLI 2023",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
booktitle = "Proceeding of the 2023 IEEE 41st Central America and Panama Convention, CONCAPAN XLI 2023",
}