Deep learning approaches for fault detection and classifications in the electrical secondary distribution network: Methods comparison and recurrent neural network accuracy comparison
The electrical power system comprises of several complex interrelated and dynamic elements, that are usually susceptible to electrical faults. Due to their critical impacts, faults on the electrical power system in the secondary distribution network should be immediately detected, classified, and ur...
Main Authors: | Daudi Mnyanghwalo, Herald Kundaeli, Ellen Kalinga, Ndyetabura Hamisi |
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Format: | Article |
Language: | English |
Published: |
Taylor & Francis Group
2020-01-01
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Series: | Cogent Engineering |
Subjects: | |
Online Access: | http://dx.doi.org/10.1080/23311916.2020.1857500 |
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