Research Article
Aircraft Gas Turbine Engine Health Monitoring System by Real Flight Data
Table 14
Details of the neural model.
| Network parameters | Details |
| Architecture | 8 inputs, 1 outputs, and 4 hidden layers with 11, 8, 4, and 3 neurons in each layer (11-8-4-3) | Set | Training subset: 70% randomly selected recorded data (9045 patterns) | Validation subset: 15% randomly selected recorded data (1935 patterns) | Test subset: 15% randomly selected recorded data (1935 patterns) | Activation | For hidden layers: tangent sigmoid tangent | Function | For output layer: linear | Training algorithm | Levenberg-Marquardt | Performance function criteria | Minimum MSE | Stopping | Validation stop | Criteria | (Training is stopped when the validation error starts increasing) |
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