On a validation split of NASA's CMAPSS FD001 data, a two-layer bidirectional LSTM with dropout predicts remaining useful life with RMSE 26.68, with no official test set evaluation.
Remaining useful life prediction of an aircraft turbofan engine using deep layer recurrent neural networks,
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Turbofan Engine Remaining Useful Life (RUL) Prediction Based on Bi-Directional Long Short-Term Memory (BLSTM)
On a validation split of NASA's CMAPSS FD001 data, a two-layer bidirectional LSTM with dropout predicts remaining useful life with RMSE 26.68, with no official test set evaluation.