Research Article
Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems
Table 2
Mean square error, root mean square error, and correlation in thirteen MLP and neuro-fuzzy networks for predicting milk EBV.
| Networks | ā | MLP | LOLIMOT | Error criteria | ā | RMSE | r | RMSE | r |
| Experiment no. | 1 | 192.3 | 0.69 | 184.022 | 0.81 | 2 | 156.5 | 0.81 | 154.5 | 0.82 | 3 | 149.8 | 0.83 | 153.4 | 0.83 | 4 | 208.1 | 0.63 | 210.6 | 0.63 | 5 | 212.0 | 0.61 | 206.8 | 0.66 | 6 | 172.8 | 0.67 | 205.5 | 0.68 | 7 | 154.1 | 0.82 | 144.2 | 0.82 | 8 | 151.6 | 0.82 | 143.1 | 0.83 | 9 | 144.3 | 0.85 | 143.4 | 0.84 | 10 | 109.7 | 0.91 | 113.1 | 0.92 | 11 | 117.9 | 0.90 | 113.0 | 0.92 | 12 | 106.7 | 0.92 | 101.8 | 0.93 | 13 | 106.2 | 0.92 | 102.0 | 0.93 |
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