Table 4.

Different parameter values evaluated for CNN optimization.

Parameter	Values/Types
Number of convolution layers	1–4
Number of pooling layers	1–3
Number of fully connected layers	1–3
Number of convolution filters	4, 8, 16, 32, 64
Dimension of convolution filters	1 × 3, 1 × 4, 1 × 5, 1 × 6, 1 × 7, 1 × 8
Number of hidden layer neurons	100, 500, 1000
Activation functions	ReLu, tanh, sigmoid
Dropout probability	0.5
Size of the batch processing	2ns, ns, $\frac{n_s}{2}$, $\frac{n_s}{4}$
Maximum number of iterations	20,000
Optimizer	Adam
Learning rate	10−4
Measure	Cross-entropy

Note: n_s: Number of IEDs.