Table 4 Fitting degree of different prediction models in segmentation of data sets with different ratios.

Model	8:1:1	7:2:1	6:3:1	7:1:2	6:2:2	5:3:2	6:1:3	5:2:3	4:3:3
Model	R²	R²	R²	R²	R²	R²	R²	R²	R²
SVR	0.8852	0.8762	0.8633	0.8232	0.8269	0.8132	0.7795	0.7487	0.7516
RFR	0.9001	0.8969	0.8425	0.8356	0.8125	0.8019	0.7851	0.7421	0.7359
MLP	0.8932	0.9061	0.8821	0.8692	0.8793	0.8611	0.7932	0.7752	0.8003
LSTM	0.9355	0.9365	0.9210	0.8716	0.8921	0.8862	0.8856	0.8236	0.8526
GRU	0.9492	0.9507	0.9315	0.8796	0.8880	0.8760	0.8569	0.8525	0.8210
ILSTM	0.9420	0.9470	0.9399	0.8890	0.8965	0.8890	0.8611	0.8499	0.8511
CNN-LSTM	0.9410	0.9487	0.9280	0.9001	0.9034	0.8962	0.8960	0.8321	0.8561
CNN-GRU	0.9498	0.9512	0.9392	0.9030	0.9164	0.8836	0.8695	0.8530	0.8312
CNN-ILSTM	0.9510	0.9638	0.9330	0.9068	0.9186	0.9020	0.8741	0.8499	0.8501

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