Skip to main content

Table 3 Performance comparison with comparative data-driven methods on Changhua dataset. It is noted that we adopt 4000 samples and 6 iterations to train the proposed model

From: SMOTE-Boost-based sparse Bayesian model for flood prediction

Methods

DC

RMSE

FPE

Han et al. [40]

0.79

96.31

210

Dawson et al. [42]

0.76

94.29

194

Chang et al. [43]

0.82

83.59

203

Lima et al. [44]

0.71

85.15

198

Wu et al. [41]

0.80

78.55

175

The proposed model

0.83

70.57

180