Research Article
Novel FTLRNN with Gamma Memory for Short-Term and Long-Term Predictions of Chaotic Time Series
Table 20
For K = 18 , training and testing samples variation for FTLRNN on testing data set for monthly sunspot time series and K = 20 for laser time series.
| Time series | Sunspot time series | Laser time series |
| Training exemplars | Testing exemplars | MSE | NMSE | | MSE | NMSE | |
| 10% | 75% | 0.01804 | 0.48780 | 0.74535 | 0.02676 | 0.80529 | 0.58788 | 20% | 65% | 0.01853 | 0.48428 | 0.75209 | 0.02361 | 0.68739 | 0.67208 | 30% | 55% | 0.01287 | 0.31169 | 0.82991 | 0.02569 | 0.79376 | 0.56198 | 40% | 45% | 0.01403 | 0.32187 | 0.83052 | 0.01659 | 0.66263 | 0.65482 | 50% | 35% | 0.02792 | 0.57914 | 0.73685 | 0.00703 | 0.30705 | 0.85539 | 60% | 25% | 0.02266 | 0.04075 | 0.7977 | 0.01635 | 0.543 | 0.71872 | 70% | 15% | 0.01885 | 0.39372 | 0.78804 | 0.03573 | 0.37992 | 0.37992 | 80% | 05% | 0.00745 | 0.21530 | 0.89769 | 0.00323 | 0.59234 | 0.59234 |
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