A novel transformer-based DL model enhanced by position-sensitive attention and gated hierarchical LSTM for aero-engine RUL prediction
Abstract Accurate prediction of remaining useful life (RUL) for aircraft engines is essential for proactive maintenance and safety assurance. However, existing methods such as physics-based models, classical recurrent neural networks, and convolutional neural networks face limitations in capturing l...
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
Nature Portfolio
2024-05-01
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| Colecção: | Scientific Reports |
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| Acesso em linha: | https://doi.org/10.1038/s41598-024-59095-3 |
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