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Improved fault classification and localization in power transmission networks using vae-generated synthetic data and machine learning algorithms

author
statement of authorship
Muhammad Amir Khan, Bilal Asad, Toomas Vaimann, Ants Kallaste, Raimondas Pomarnacki, Van Khang Hyunh
source
special issue
Machine Learning and Artificial Intelligence in Machinery Condition Monitoring
publisher
journal volume number month
vol. 11, 10
year of publication
pages
art. 963
url
ISSN
2075-1702
notes
Bibliogr.: 44 ref
Open Access
Open Access
scientific publication
teaduspublikatsioon
language
inglise
subject term
keyword
electrical power systems
support vector machines
random forest
machine learning
wavelet transform
transmission lines fault
electrical power quality
short circuit
classification of faults
localization of faults
decision trees
ensemble learning
k-nearest neighbors
Reserch Group
Electrical machines research group
Khan, M. A., Asad, B., Vaimann, T., Kallaste, A., Pomarnacki, R., Hyunh, V. K. Improved fault classification and localization in power transmission networks using vae-generated synthetic data and machine learning algorithms // Machines (2023) vol. 11, 10, art. 963. https://doi.org/10.3390/machines11100963