Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm

Bibliographic Details
Main Author: Frontiers Production Office
Format: Article
Language:English
Published: Frontiers Media S.A. 2023-08-01
Series:Frontiers in Energy Research
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fenrg.2023.1281611/full
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author Frontiers Production Office
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spelling doaj.art-7b4f6918ee794511b29f5e19a4d3d6e12023-08-31T16:16:37ZengFrontiers Media S.A.Frontiers in Energy Research2296-598X2023-08-011110.3389/fenrg.2023.12816111281611Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithmFrontiers Production Officehttps://www.frontiersin.org/articles/10.3389/fenrg.2023.1281611/fullgenerative adversarial networksfew sampleReptile algorithmmeta learninghigh impedance faultevolution strategy
spellingShingle Frontiers Production Office
Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
Frontiers in Energy Research
generative adversarial networks
few sample
Reptile algorithm
meta learning
high impedance fault
evolution strategy
title Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
title_full Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
title_fullStr Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
title_full_unstemmed Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
title_short Erratum: An evolution strategy of GAN for the generation of high impedance fault samples based on Reptile algorithm
title_sort erratum an evolution strategy of gan for the generation of high impedance fault samples based on reptile algorithm
topic generative adversarial networks
few sample
Reptile algorithm
meta learning
high impedance fault
evolution strategy
url https://www.frontiersin.org/articles/10.3389/fenrg.2023.1281611/full
work_keys_str_mv AT frontiersproductionoffice erratumanevolutionstrategyofganforthegenerationofhighimpedancefaultsamplesbasedonreptilealgorithm