Table 20 Models’ performance scores based on Sungai Klang test set.

From: Predicting streamflow in Peninsular Malaysia using support vector machine and deep learning algorithms

Model

MAE

RMSE

R2

Rank (MAE)

Rank (RMSE)

Rank (R2)

RM

SVR1

3.8143

6.7184

− 0.0712

1

2

2

1.67

SVR2

3.9975

6.8580

− 0.1162

3

3

3

3.00

SVR3

3.8568

6.6737

− 0.0570

2

1

1

1.33

ANN1

5.2573

7.5966

− 0.3696

5

5

8

6.00

ANN2

5.0754

7.4943

− 0.3329

4

4

6

4.67

ANN3

6.0143

8.1951

− 0.5939

6

9

9

8.00

LSTM1

6.7049

7.8051

− 0.3499

9

8

7

8.00

LSTM2

6.4877

7.6416

− 0.2939

8

7

5

6.67

LSTM3

6.4529

7.6092

− 0.2830

7

6

4

5.67

  1. Significant values are in bold.