Table 12 Forecasting performance of deep learning models after feature selection (wind forecasting).

From: Optimizing solar and wind forecasting with iHow optimization algorithm and multi-scale attention networks

Model

MSE

RMSE

MAE

MBE

\(\varvec{r}\)

\(\varvec{R^2}\)

RRMSE

NSE

WI

MSAN

0.0018

0.0007

0.0007

0.0006

0.8916

0.9042

15.44

0.8906

0.8860

LSTM

0.0275

0.0108

0.0103

0.0168

0.8518

0.8644

17.64

0.8814

0.7825

GRU

0.0782

0.0122

0.0110

0.0190

0.7445

0.7571

18.48

0.8443

0.7266

GANT

0.0822

0.0135

0.0122

0.0196

0.7081

0.7207

19.06

0.8202

0.6626

ARN

0.0866

0.0140

0.0127

0.1078

0.6896

0.7021

19.49

0.7943

0.5962

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