Table 5.
Mean absolute error for artificial dataset.
Method | Set | Average Value | Minimum Value | Maximum Value | Standard Deviation |
---|---|---|---|---|---|
Seasonal ARIMA | Training | 14.148 | NA | ||
Test | 13.644 | ||||
Support vector regression | Training | 0.132 * | NA | ||
Test | 8.541 | ||||
Multi-layer perceptron | Training | 1.552 | 0.399 | 5.461 | 1.570 |
Test | 8.283 | 7.595 | 10.173 | 0.724 | |
Convolutional neural network | Training | 0.580 | 0.221 | 0.867 | 0.238 |
Test | 10.012 | 9.711 | 10.319 | 0.190 | |
LSTM-EEMD | Training | 17.750 | 16.628 | 19.368 | 1.435 |
Test | 18.308 | 17.658 | 19.382 | 0.937 | |
LSTM RNN many-to-one | Training | 15.591 | 8.107 | 29.257 | 6.113 |
Test | 17.447 | 8.327 | 29.060 | 7.196 | |
LSTM RNN many-to-many | Training | 8.521 | 8.519 | 8.524 | 0.001 |
Test | 7.984 * | 7.965 | 7.990 | 0.007 |
*: Best result.