Comparative analysis of data-driven models on detection and classification of electrical faults in transmission systems: Explainability, applicability and industrial implications
Most data-driven fault detection methods often face challenges in accuracy, adaptability, and real-time implementation, particularly in complex transmission networks. To address these issues, this study presents an in-depth comparative analysis of data-driven models, including machine learning, neur...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-08-01
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| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016825005848 |
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