Research Article
Research and Application of a New Hybrid Forecasting Model Based on Genetic Algorithm Optimization: A Case Study of Shandong Wind Farm in China
Table 4
The forecasting results and optimized parameters of the proposed hybrid model EEMD-GA-FAC/SAC in site 1.
| ā | ā | | Time | Actual value (m/s) | Forecasting value (m/s) | MAPE (%) | MSE (m2/s2) | MAE (m/s) |
| Observation site 1 | EEMD-GA-FAC | 0.1729 | 0:00 | 6.7 | 6.70 | 0.00 | 0.0000 | 0.0001 | 0.0000 | 2:00 | 8.4 | 7.77 | 7.50 | 0.3974 | 0.6304 | 0.5587 | 4:00 | 8.5 | 7.93 | 6.75 | 0.3293 | 0.5739 | 0.0000 | 6:00 | 6.9 | 7.10 | 2.89 | 0.0396 | 0.1991 | 0.1777 | 8:00 | 6.8 | 6.80 | 0.00 | 0.0000 | 0.0000 | 0.2059 | 10:00 | 6.9 | 6.90 | 0.00 | 0.0000 | 0.0000 | 0.9994 | 12:00 | 8.3 | 8.01 | 3.47 | 0.0828 | 0.2877 | 0.1445 | 14:00 | 10.6 | 10.60 | 0.00 | 0.0000 | 0.0000 | 0.0000 | 16:00 | 9.6 | 9.76 | 1.66 | 0.0253 | 0.1591 | 0.1927 | 18:00 | 11.7 | 11.70 | 0.00 | 0.0000 | 0.0001 | 0.0000 | 20:00 | 10.3 | 10.33 | 0.34 | 0.0012 | 0.0345 | 0.0191 | 22:00 | 12 | 10.22 | 14.80 | 3.1527 | 1.7756 | EEMD-GA-SAC | 0.1889 | 0:00 | 6.7 | 6.70 | 0.00 | 0.0000 | 0.0001 | 0.0000 | 2:00 | 8.4 | 8.03 | 4.39 | 0.1363 | 0.3692 | 0.5637 | 4:00 | 8.5 | 7.93 | 6.75 | 0.3295 | 0.5740 | 0.0000 | 6:00 | 6.9 | 7.01 | 1.61 | 0.0124 | 0.1113 | 0.1981 | 8:00 | 6.8 | 6.80 | 0.00 | 0.0000 | 0.0000 | 0.2228 | 10:00 | 6.9 | 6.90 | 0.00 | 0.0000 | 0.0001 | 0.0000 | 12:00 | 8.3 | 8.02 | 3.40 | 0.0795 | 0.2819 | 0.1386 | 14:00 | 10.6 | 10.60 | 0.00 | 0.0000 | 0.0000 | 0.0018 | 16:00 | 9.6 | 9.58 | 0.23 | 0.0005 | 0.0217 | 0.1993 | 18:00 | 11.7 | 11.70 | 0.00 | 0.0000 | 0.0000 | 1.0000 | 20:00 | 10.3 | 10.33 | 0.34 | 0.0012 | 0.0345 | 0.0201 | 22:00 | 12 | 10.25 | 14.61 | 3.0736 | 1.7532 |
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