Support Vector Regression Based on Grid-Search Method for Short-Term Wind Power Forecasting
Table 3
Simulation results refer to multiscale SVR.
Item
BCVM
Bc
Bg
Foin
RM
RS
RBF(3)
O
0.00121642
1024
0.00195313
3465
0.00383891
0.943034
M
0.00118972
64
0.015625
1756
0.00194981
0.972598
W
0.00217458
0.5
1
1628
0.0211323
0.897533
PF(3)
O
0.00121642
1024
0.00195313
4365
0.00383891
0.943034
M
0.00118972
64
0.015625
2756
0.00194981
0.972598
W
0.00217458
0.5
1
1628
0.0211323
0.897533
RBF(6)
O
0.00117004
1024
0.00390625
4562
0.00381612
0.94281
M
0.0010876
128
0.00390625
2810
0.00189855
0.972905
W
0.0021321
0.5
1
1534
0.0219367
0.895725
PF(6)
O
0.00117004
1024
0.00390625
4562
0.00381612
0.94281
M
0.0010876
128
0.00390625
2810
0.00189855
0.972905
W
0.0021321
0.5
1
1534
0.0219367
0.895725
RBF(10)
O
0.0011804
512
0.00195313
5366
0.00381804
0.94289
M
0.00107203
128
0.00390625
2441
0.00191227
0.972918
W
0.00217458
0.5
1
1534
0.0219367
0.895725
PF(10)
O
0.0011804
512
0.00195313
5366
0.00381804
0.94289
M
0.00107203
128
0.00390625
2441
0.00191227
0.972918
W
0.00214353
0.5
1
1534
0.0219367
0.895725
O: original data; M: MAD filter; W: wavelet filter; RBF(3): number of cross-validation for testing set is 3 by RBF, similar to RBF(6) and RBF(10); PF(3): number of cross-validation for testing set is 3 by PF, similar to PF(6) and PF(10); BCVM: best cross-validation mean squared error; Bc: best c; Bg: best g; Foin: finished optimization iteration number; RM: regression mean squared error; RS: regression squared correlation coefficient.
