Research Article
Prediction of Mechanical Properties of Aluminium Alloy Strip Using the Extreme Learning Machine Model Optimized by the Gray Wolf Algorithm
Table 7
Comparison of the predictive performance of the three models.
| Mechanical properties | Name | RMSE | MAPE | R2 | Train set | Test set | Train set | Test set | Train set | Test set |
| Tensile strength | GWO-ELM | 9.052 | 5.365 | 1.951 | 1.703 | 0.9549 | 0.9857 | MGWO-ELM | 7.939 | 11.557 | 1.574 | 2.316 | 0.9534 | 0.9805 | ELM | 10.976 | 21.489 | 2.702 | 5.317 | 0.9386 | 0.7102 |
| Yield strength | GWO-ELM | 15.499 | 11.881 | 4.204 | 2.703 | 0.9303 | 0.9662 | MGWO-ELM | 16.795 | 20.465 | 4.225 | 5.185 | 0.9022 | 0.9804 | ELM | 19.163 | 43.313 | 6.176 | 16.165 | 0.9053 | 0.3958 |
| Elongation | GWO-ELM | 1.424 | 1.268 | 7.371 | 5.994 | 0.7649 | 0.9141 | MGWO-ELM | 1.355 | 1.845 | 6.937 | 9.244 | 0.8123 | 0.9074 | ELM | 1.630 | 5.360 | 8.864 | 19.630 | 0.7384 | ā0.8312 |
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