Research Article
A New Hybrid Model Based on an Intelligent Optimization Algorithm and a Data Denoising Method to Make Wind Speed Predication
Table 10
Comprehensive comparison of the performances of models involved.
| | Model | MAE (m/s) | Improvement (%) | MSE (m2/s2) | Improvement (%) | MAPE (%) | Improvement (%) | Running time (s) |
| | BPANN | 0.4284 | 24.70 | 0.3461 | 45.25 | 8.7525 | 21.28 | 1.14 | | ARIMA | 0.4330 | 25.50 | 0.3522 | 46.20 | 8.74 | 21.17 | 38.0052 | | AFSA-BPANN | 0.4289 | 24.78 | 0.3446 | 45.01 | 8.8183 | 21.87 | 105.9424 | | WT-BPANN | 0.4281 | 24.64 | 0.3482 | 45.58 | 8.6233 | 20.1 | 1.4398 | | WT-ARIMA | 0.4332 | 25.53 | 0.3571 | 46.93 | 8.6691 | 20.52 | 39.4098 | | WAFSA-BPANN | 0.3226 | — | 0.1895 | — | 6.89 | — | 146.8031 |
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