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English Information

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Authors
# Name
1 Patrick Karvat(patrickkarvat.pk@ufpr.br)
2 Eduardo Almeida(eduardo.almeida@ufpr.br)
3 Leandro Ensina(leandro.ensina@ufpr.br)
4 Luiz Oliveira(luiz.oliveira@ufpr.br)
5 Signie Santos(signie_s@hotmail.com)
6 Leandro Bernardino(leandro.bernardino@copel.com)

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Reference
# Reference
1 Belagoune, S., Bali, N., Bakdi, A., Baadji, B., and Atif, K. (2021). Deep learning through lstm classification and regression for transmission line fault detection, diagnosis and location in large-scale multi-machine power systems. Measurement, 177:109330.
2 Bichels, A. (2018). Sistemas Elétricos de Potência — Métodos de Análise e Solução. EDUTFPR.
3 Brownlee, J. (2020). Data Preparation for Machine Learning: Data Cleaning, Feature Selection, and Data Transforms in Python, pages 25 – 36. Machine Learning Mastery.
4 Chen, Y. Q., Fink, O., and Sansavini, G. (2018). Combined fault location and classification for power transmission lines fault diagnosis with integrated feature extraction. IEEE Transactions on Industrial Electronics, 65(1):561–569.
5 Cho, K., van Merrienboer, B., Bahdanau, D., and Bengio, Y. (2014). On the properties of neural machine translation: Encoder-decoder approaches. CoRR, abs/1409.1259.
6 Ensina, L. A. (2021). Fault analysis database. https://1drv.ms/u/s!ArMEeMx4MYDNimHVxiDx3b4CI3iL?e=8GfXg7. Acessado em 30/12/2021.
7 Hochreiter, S. and Schmidhuber, J. (1997). Long short-term memory. Neural Computation, 9(8):1735–1780.
8 Kaufman, S., Rosset, S., Perlich, C., and Stitelman, O. (2012). Leakage in data mining: Formulation, detection, and avoidance. ACM Trans. Knowl. Discov. Data, 6(4).
9 Radiuk, P. (2017). Impact of training set batch size on the performance of convolutional neural networks for diverse datasets. Information Technology and Management Science, 20:20–24.
10 Ray, P. and Mishra, D. P. (2016). Support vector machine based fault classification and location of a long transmission line. Engineering Science and Technology, an International Journal, 19(3):1368–1380.
11 Singh, S. and Vishwakarma, D. N. (2015). Intelligent techniques for fault diagnosis in ransmission lines — an overview. In International Conference on Recent Developments in Control, Automation and Power Engineering (RDCAPE), pages 280–285.
12 Yadav, A. and Dash, Y. (2014). An overview of transmission line protection by artificial neural network: Fault detection, fault classification, fault location, and fault direction discrimination. Advances in Artificial Neural Systems, 2014:1–20.
13 Zhang, F., Liu, Q., Liu, Y., Tong, N., Chen, S., and Zhang, C. (2020). Novel fault location method for power systems based on attention mechanism and double structure gru neural network. IEEE Access, 8:75237–75248.