Table 3 Comparison of SMI-TCN-BILSTM with other neural network models.

From: Optimization of TCN-BiLSTM for dissolved oxygen prediction based on improved sparrow search algorithm

Model

MSE

RMSE

MAE

MAPE

R2

BP34

0.1005

0.317

0.2487

2.85%

88.00%

SVR35

0.0331

0.1820

0.1475

1.74%

96.05%

LSTM9

0.0286

0.1692

0.1215

1.38%

96.58%

TCN-LSTM33

0.0433

0.2081

0.1446

1.69%

94.83%

CNN-LSTM36

0.0293

0.1711

0.1316

1.52%

96.50%

CNN-GRU-Attention14

0.0302

0.1738

0.1339

1.53%

96.39%

BiLSTM11

0.0247

0.1571

0.1180

1.35%

97.05%

TCN-BiLSTM

0.0245

0.1566

0.1148

1.32%

97.07%

SSA-TCN-BiLSTM

0.0225

0.1501

0.1082

1.23%

97.31%

SMI-TCN-BiLSTM(Ours)

0.0132

0.1147

0.0851

0.96%

98.43%

  1. The model input data in the above tables are processed with Savitzky-Golay filter and MIC to ensure fairness of the prediction results.
Back to article page