Research Article
Temperature Prediction of Photovoltaic Panels Based on Support Vector Machine with Pigeon-Inspired Optimization
Table 2
Comparison of prediction accuracy for NARMA.
| Method | Optimized parameters | MSE | RMSE | Accuracy improvement (%) | | |
| SVM | 0.1 | 1 | 1.0155e − 05 | 3.187e − 03 | — | DE-SVM | 1.8581 | 13.3556 | 1.0340e − 05 | 3.216e − 03 | −1.82 | PSO-SVM | 0.0719 | 7.9756 | 1.0141e − 05 | 3.184e − 03 | 0.13 | PIO-SVM | 0.6372 | 12.5727 | 1.0140e − 05 | 3.184e − 03 | 0.14 | OPIO-SVM | 0.0772 | 13.4447 | 1.0075e − 05 | 3.174e − 03 | 0.79 | DFPIO-SVM | 0.0130 | 10.0047 | 9.9202e − 06 | 3.150e − 03 | 2.31 |
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