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Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks.

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Title: Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks.
Authors: Bramareswara Rao, S. N. V.1 (AUTHOR) snvbrao.eee@sircrrengg.ac.in, Kumar, Y. V. Pavan2 (AUTHOR) pavankumar.yv@vitap.ac.in, Amir, Mohammad3 (AUTHOR) md.amir@ieee.org, Muyeen, S. M.4 (AUTHOR) sm.muyeen@qu.edu.qa
Source: Electrical Engineering. Jul2025, Vol. 107 Issue 7, p8481-8498. 18p.
Database: Academic Search Ultimate
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  Data: Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks.
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  Data: <searchLink fieldCode="JN" term="%22Electrical+Engineering%22">Electrical Engineering</searchLink>. Jul2025, Vol. 107 Issue 7, p8481-8498. 18p.
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=asn&AN=187262569
RecordInfo BibRecord:
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        Value: 10.1007/s00202-024-02329-4
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      – Code: eng
        Text: English
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      – TitleFull: Fault detection and classification in hybrid energy-based multi-area grid-connected microgrid clusters using discrete wavelet transform with deep neural networks.
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            NameFull: Bramareswara Rao, S. N. V.
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              M: 07
              Text: Jul2025
              Type: published
              Y: 2025
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              Value: 107
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