Research Article
Novel FTLRNN with Gamma Memory for Short-Term and Long-Term Predictions of Chaotic Time Series
Table 18
For K = 6, training and testing samples variation for FTLRNN on testing data set for monthly sunspot time series and K = 5 for laser time series.
| Time series | Sunspot time series Months | Laser time series |
| Training exemplars | Testing exemplars | MSE | NMSE | | MSE | NMSE | |
| 10% | 75% | 0.00707 | 0.19197 | 0.91703 | 0.00782 | 0.24068 | 0.87439 | 20% | 65% | 0.00451 | 0.11888 | 0.94153 | 0.00811 | 0.23969 | 0.88027 | 30% | 55% | 0.00423 | 0.10308 | 0.94712 | 0.00808 | 0.24814 | 0.87504 | 40% | 45% | 0.00438 | 0.10197 | 0.95081 | 0.00635 | 0.25307 | 0.87748 | 50% | 35% | 0.00654 | 0.13744 | 0.94252 | 0.00267 | 0.12898 | 0.94513 | 60% | 25% | 0.00554 | 0.1008 | 0.95528 | 0.00372 | 0.13558 | 0.93962 | 70% | 15% | 0.00473 | 0.10259 | 0.95359 | 0.00534 | 0.14838 | 0.92717 | 80% | 05% | 0.00499 | 0.15725 | 0.92195 | 0.01579 | 0.34297 | 0.83272 |
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