Classification of lightning stroke on transmission line using multi-resolution analysis and machine learning
• Classification of lightning stroke with and without fault is presented. • Multi-resolution analysis and machine learning are used. • The most important parameters of lightning are considered. • Comparative evaluation using five mother wavelets is presented. • Multi-resolution analysis is recommend...
Ausführliche Beschreibung
Gespeichert in:
| Autor*in: |
Morales, J.A. [verfasserIn] |
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| Format: |
E-Artikel |
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| Sprache: |
Englisch |
| Erschienen: |
2014 |
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| Schlagwörter: |
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| Umfang: |
13 |
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| Übergeordnetes Werk: |
Enthalten in: Synthesis and characterization of AsO[(W,Mo)O - Goudjil, Meriem ELSEVIER, 2023, Amsterdam [u.a.] |
|---|---|
| Übergeordnetes Werk: |
volume:58 ; year:2014 ; pages:19-31 ; extent:13 |
| Links: |
|---|
| DOI / URN: |
10.1016/j.ijepes.2013.12.017 |
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| 520 | |a • Classification of lightning stroke with and without fault is presented. • Multi-resolution analysis and machine learning are used. • The most important parameters of lightning are considered. • Comparative evaluation using five mother wavelets is presented. • Multi-resolution analysis is recommended. | ||
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Classification of lightning stroke on transmission line using multi-resolution analysis and machine learning |
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• Classification of lightning stroke with and without fault is presented. • Multi-resolution analysis and machine learning are used. • The most important parameters of lightning are considered. • Comparative evaluation using five mother wavelets is presented. • Multi-resolution analysis is recommended. |
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