Table 4 Comparative outcomes of all models of different comparative models with 180 participating clients.

From: Optimizing electric load forecasting with support vector regression/LSTM optimized by flexible Gorilla troops algorithm and neural networks a case study

 

RMSE

MAPE

Method

Max

Min

Mean

Max

Min

Mean

SVR 28

2.721

0.075

0.734

81.49%

11.23%

42.01%

LSTM 29

2.630

0.074

0.725

80.14%

11.22%

40.10%

NN/GSOA 30

2.784

0.075

0.727

84.54%

11.79%

42.56%

SVR/LSTM 31

2.671

0.048

0.685

88.74%

10.21%

39.68%

VMD/ELM/DE 32

2.667

0.045

0.661

85.65%

10.17%

39.08%

SVR/LSTM/FGTO

2.650

0.042

0.641

84.35%

10.11%

38.40%

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