Research Article
A New Hybrid Model Based on an Intelligent Optimization Algorithm and a Data Denoising Method to Make Wind Speed Predication
Table 5
The forecasting results of October from observation site 1 on a given time interval.
| Date
October | Time (h) | Actual value | BPANN | ARIMA | WT-ARIMA | WAFSA-BPANN | | Forecasting | MAPE (%) | Forecasting | MAPE (%) | Forecasting | MAPE (%) | Forecasting | MAPE (%) |
| | Oct. 2 | 0:00
6:00
12:00
18:00 | 7.5
8.5
9.1
10.7 | 7.452
8.185
9.412
11.173 | 0.645
3.706
3.431
4.423 | 7.384
8.129
9.422
10.695 | 1.541
4.368
3.543
0.051 | 6.322
8.368
9.511
10.442 | 15.709
1.548
4.513
2.408 | 7.160
7.955
9.228
10.988 | 4.527
6.406
1.408
2.690 |
| | Oct. 3 | 0:00
6:00
12:00
18:00 | 10.5
6.5
5.7
4.4 | 11.719
6.817
5.273
4.188 | 11.610
4.883
7.492
4.818 | 11.723
6.912
5.344
4.166 | 11.649
6.337
6.247
5.316 | 11.765
6.770
5.082
4.199 | 12.052
4.148
10.841
4.571 | 10.970
7.017
5.796
4.207 | 4.480
7.957
1.683
4.394 |
| | Oct. 4 | 0:00
6:00
12:00
18:00 | 3.8
3.3
3.1
2.9 | 4.424
3.432
3.176
2.579 | 16.428
3.986
2.442
11.065 | 4.477
3.353
2.955
2.474 | 17.817
1.592
4.673
14.683 | 4.434
3.392
3.075
2.476 | 16.675
2.781
0.795
14.619 | 4.179
3.212
2.574
2.667 | 9.983
2.677
16.962
8.043 |
| | Oct. 5 | 0:00
6:00
12:00
18:00 | 4.3
3.8
6.6
7.5 | 4.483
3.921
6.225
6.712 | 4.267
3.187
5.685
10.508 | 4.449
3.918
6.190
6.557 | 3.459
3.114
6.214
12.568 | 4.499
3.894
6.159
6.865 | 4.622
2.481
6.687
8.468 | 4.317
4.034
6.106
7.105 | 0.392
6.146
7.480
5.272 |
| | Oct. 6 | 0:00
6:00
12:00
18:00 | 9.4
8.6
6.8
4.2 | 8.985
8.160
7.209
4.300 | 4.412
5.116
6.008
2.391 | 8.982
8.164
7.286
4.402 | 4.450
5.067
7.140
4.814 | 9.020
8.075
7.216
4.275 | 4.038
6.103
6.119
1.794 | 9.024
8.192
7.328
4.621 | 4.000
4.740
7.765
10.013 |
| | Oct. 7 | 0:00
6:00
12:00
18:00 | 3.9
2.6
3.1
4.6 | 4.456
2.573
3.502
4.641 | 14.266
1.038
12.952
0.884 | 4.519
2.512
3.448
4.675 | 15.864
3.398
11.232
1.624 | 4.371
2.484
3.519
4.632 | 12.067
4.467
13.511
0.689 | 4.354
2.441
3.046
4.670 | 11.645
6.111
1.744
1.522 |
|
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