| Title: | Most influential feature form for supervised learning in voltage sag source localization |
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| Authors: | ID Mohammadi, Younes (Author)
ID Polajžer, Boštjan (Author)
ID Chouhy Leborgne, Roberto (Author)
ID Khodadad, Davood (Author) |
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| Files: |  1-s2.0-S0952197624004895-main.pdf (15,94 MB)
MD5: 3DDA8D3E768F62296CBC8B106198650C
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FERI - Faculty of Electrical Engineering and Computer Science
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| Keywords: | voltage sag (dip), source localization, supervised and unsupervised learning, convolutional neural network, time-sample-based features |
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| Submitted for review: | 15.03.2024 |
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| Article acceptance date: | 23.03.2024 |
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| Publication date: | 02.04.2024 |
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| Year of publishing: | 2024 |
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| Number of pages: | 29 str. |
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| Numbering: | vol. 133, [article no.] 108331 |
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| PID: | 20.500.12556/DKUM-90152  |
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| UDC: | 621.31 |
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| ISSN on article: | 1873-6769 |
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| COBISS.SI-ID: | 191325699 |
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| DOI: | 10.1016/j.engappai.2024.108331 |
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| Publication date in DKUM: | 23.08.2024 |
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| Views: | 65 |
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| Downloads: | 5 |
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| Metadata: |    |
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| Categories: | Misc.
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