Table 3
Comparison between flow fields vD,t and vref,t for the ARs dataset. RMSE is the root mean squared error (Eq. (1)), Eabs is the mean absolute error (Eq. (2)), Erel is the mean relative error (Eq. (3)), C is the correlation coefficient (Eq. (4)), A is the spatially-averaged normalized dot product (Eq. (5)) and S is the ratio between the integrals of the unsigned shear components of the DeepVel and reference Poynting fluxes (Eq. (9)).
| Training set (ARs dataset) | Quantity (units) | |Bref,z| (G) | RMSE | Eabs | Erel (%) | C ∈ [0, 1] | A ∈ [−1, 1] | S (no units) |
|---|---|---|---|---|---|---|---|---|
| STAGGER (τ ≈ 1) | vt (km s−1) | ≥0 | 1.297 | 1.029 | 102.6 | 0.653 | 0.630 | 0.213 |
| <100 | 1.264 | 1.006 | 78.44 | 0.692 | 0.676 | – | ||
| ≥100 | 1.604 | 1.267 | 353.2 | 0.166 | 0.155 | – | ||
| MURaM-ARs (τ ≈ 1) | vt (km s−1) | ≥0 | 0.719 | 0.603 | 70.98 | 0.905 | 0.830 | 1.061 |
| <100 | 0.701 | 0.592 | 56.02 | 0.912 | 0.855 | – | ||
| ≥100 | 0.878 | 0.717 | 226.2 | 0.845 | 0.563 | – | ||
| MURaM-ARs (τ ≈ 0.1) | vt (km s−1) | ≥0 | 0.798 | 0.663 | 76.17 | 0.867 | 0.785 | 1.459 |
| <100 | 0.793 | 0.662 | 61.51 | 0.878 | 0.824 | – | ||
| ≥100 | 0.840 | 0.678 | 217.9 | 0.639 | 0.410 | – | ||
| MURaM-ARs (τ ≈ 0.01) | vt (km s−1) | ≥0 | 0.887 | 0.731 | 106.5 | 0.660 | 0.585 | 1.038 |
| <100 | 0.880 | 0.728 | 91.03 | 0.680 | 0.619 | – | ||
| ≥100 | 0.956 | 0.759 | 253.9 | 0.415 | 0.261 | – | ||
| MURaM-ARs (τ ≈ 0.001) | vt (km s−1) | ≥0 | 1.114 | 0.912 | 127.5 | 0.331 | 0.208 | 0.996 |
| <100 | 1.104 | 0.913 | 118.6 | 0.281 | 0.199 | – | ||
| ≥100 | 1.214 | 0.893 | 225.9 | 0.580 | 0.306 | – | ||
| MURaM-ARs (d = 1000 km) | vt (km s−1) | ≥0 | 0.961 | 0.851 | 152.9 | 0.258 | 0.164 | 1.343 |
| <100 | 0.980 | 0.876 | 149.2 | 0.258 | 0.159 | – | ||
| ≥100 | 0.762 | 0.619 | 187.1 | 0.257 | 0.215 | – |
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