Table 3
Initial settings of the EPR-MOGA analysis and the data overview
| Parameters | EPR-MOGA setting | ||
|---|---|---|---|
| Case 1: Mean temperature | Case 2: Temperature half-thickness | Case 3: Spread of jet across the channel | |
| Regression type | Linear regression | ||
| Polynomial structure |  | ||
| Inner function type | No function | ||
| Constant estimation method | Least square | ||
| Range of exponents | [−2, −1.5, −1, −0.5, 0, 0.5, 1, 1.5, 2] | ||
| Maximum number of terms | [1:100] | [1:30] | [1:30] |
| Number of data | 1,634 | 1,632 | 34 |
| Number of training data | 817 | 816 | 17 |
| Number of testing data | 817 | 816 | 17 |
| Input variables | (x, y, z), R, d, T0 | (x), R, d, T0 | (x,y), R, d, T0 |
| Output variables | T | H | S |
| Parameters | EPR-MOGA setting | ||
|---|---|---|---|
| Case 1: Mean temperature | Case 2: Temperature half-thickness | Case 3: Spread of jet across the channel | |
| Regression type | Linear regression | ||
| Polynomial structure | | ||
| Inner function type | No function | ||
| Constant estimation method | Least square | ||
| Range of exponents | [−2, −1.5, −1, −0.5, 0, 0.5, 1, 1.5, 2] | ||
| Maximum number of terms | [1:100] | [1:30] | [1:30] |
| Number of data | 1,634 | 1,632 | 34 |
| Number of training data | 817 | 816 | 17 |
| Number of testing data | 817 | 816 | 17 |
| Input variables | (x, y, z), R, d, T0 | (x), R, d, T0 | (x,y), R, d, T0 |
| Output variables | T | H | S |