Neural network architecture and genetic algorithm hyperparameters used in the proposed GA-optimized PINN framework
| Parameter | Value |
|---|---|
| Network layers | 3 |
| Neurons per layer | 64 |
| Activation function | Tanh |
| Optimizer | Adam |
| Collocation points per epoch | 1,200 |
| GA population size | 10 |
| GA generations | 12 |
| Short training epochs (GA evaluation) | 400 |
| Full training epochs (final model) | 1,500 |
| Parameter | Value |
|---|---|
| Network layers | 3 |
| Neurons per layer | 64 |
| Activation function | Tanh |
| Optimizer | Adam |
| Collocation points per epoch | 1,200 |
| GA population size | 10 |
| GA generations | 12 |
| Short training epochs (GA evaluation) | 400 |
| Full training epochs (final model) | 1,500 |
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