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)