Research Article
Sequential Network with Residual Neural Network for Rotatory Machine Remaining Useful Life Prediction Using Deep Transfer Learning
Table 4
RMSE results of hand-out cross validation.
| | Method | Dataset | | 1–3 | 1–4 | 2–2 | 2–4 | 3–3 | 3–4 |
| | RNN | 112.14 (19.64) | 109.32 (15.22) | 112.58 (16.26) | 126.63 (19.48) | 135.47 (24.71) | 132.19 (20.25) | | GRU | 65.28 (9.99) | 78.19 (8.47) | 68.51 (11.21) | 65.11 (9.77) | 71.69 (11.76) | 88.45 (9.49) | | Bi-LSTM | 55.79 (8.87) | 59.63 (8.62) | 48.51 (9.94) | 54.36 (9.92) | 57.78 (10.23) | 67.98 (17.53) | | ResSN-TL | 37.26 (7.63) | 38.12 (8.48) | 30.25 (7.12) | 38.97 (6.25) | 42.36 (7.97) | 47.38 (7.74) |
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