Table 5.
Summary of the MLP neural network design approach.
| Thermoplastic Material | PVC |
|---|---|
| Number of datasets | 42 |
| Training dataset | 36 |
| Validation dataset | 6 |
| Training Algorithm | Levenberg Marquardt |
| Activation Function | Tansig and Purelin |
| Training Time | 5 s |
| Number of Iterations | 6 iterations |
| Performance Evaluation | Mean Square Error |
| Number of Inputs Layers | 1 |
| Number of Input Neurons | 9 (represents the properties for different grades of PVC thermoplastic) |
| Number of Hidden Layers | 2 |
| Number of Hidden Neurons (1st layer) | 50 |
| Number of Hidden Neurons (2nd layer) | 40 |
| Number of Output Layer | 1 |
| Number of Output Neuron | 11 (represents output variable, i.e. profile settings) |