Following the selection of the ANN models' prerequisites, six ANN models were developed to estimate coastal current velocities for the three conditions of interest. The main factor in the FFBP is the number of hidden neurons (NHN) and is reported in Table 6. To tune this parameter, several numbers of hidden neurons were examined. Note that the RMSE of both training and validation data sets are reported in the table along with desired epochs.
Table 6
Characteristics of ANN models to estimate coastal current velocities for different conditions
| Condition | Desired epoch | NHN | Validation error (m/s) | Training error (m/s) | |
|---|---|---|---|---|---|
| General | 11 | 200 | 0.0534 | 0.0501 | |
| General | 23 | 200 | 0.0823 | 0.0797 | |
| Stormy | 9 | 200 | 0.0631 | 0.041 | |
| Stormy | 12 | 200 | 0.1031 | 0.117 | |
| Windy | 7 | 200 | 0.0489 | 0.0434 | |
| Windy | 10 | 200 | 0.0545 | 0.0672 |
| Condition | Desired epoch | NHN | Validation error (m/s) | Training error (m/s) | |
|---|---|---|---|---|---|
| General | 11 | 200 | 0.0534 | 0.0501 | |
| General | 23 | 200 | 0.0823 | 0.0797 | |
| Stormy | 9 | 200 | 0.0631 | 0.041 | |
| Stormy | 12 | 200 | 0.1031 | 0.117 | |
| Windy | 7 | 200 | 0.0489 | 0.0434 | |
| Windy | 10 | 200 | 0.0545 | 0.0672 |