A Sequence-to-Sequence Approach for Remaining Useful Lifetime Estimation Using Attention-augmented Bidirectional LSTM
We propose a novel sequence-to-sequence prediction approach for the estimation of the remaining useful lifetime (RUL) of technical components. The approach is based on deep recurrent neural network structures, namely bidirectional Long Short Term Memory (LSTM) networks, which we augment with an atte...
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| Huvudupphov: | , , , |
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| Materialtyp: | Artigo |
| Språk: | Inglês |
| Utgiven: |
Elsevier
2021-07-01
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| Serie: | Intelligent Systems with Applications |
| Ämnen: | |
| Länkar: | http://www.sciencedirect.com/science/article/pii/S2667305321000387 |
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