Table 4 Prediction RMSE of the three methods on each test set.

From: High-precision prediction method for mine deformation based on GNSS RTK and stacking ensemble learning

Metrics

Survey station

Comparative method 1 (/m)

Comparative method 2 (/m)

Proposed method (/m)

RMSE

NPS7602

0.028003

0.029621

0.000574

WPE7206

0.031684

0.021663

0.000453

WPS7403

0.003620

0.031476

0.000765

WPE7604

0.002708

0.021525

0.000556

NPS6801

0.009653

0.025734

0.000283

Mean

0.015134

0.026004

0.000526

ME

NPS7602

0.045324

0.076836

0.002179

WPE7206

0.056786

0.079198

0.001879

WPS7403

0.012136

0.082946

0.002596

WPE7604

0.009478

0.078562

0.002113

NPS6801

0.015445

0.080125

0.001094

Mean

0.027834

0.079533

0.001972

95% confidence interval based on the Z-distribution

NPS7602

[0.025358, 0.026618]

[0.023503, 0.025512]

[0.000418, 0.000463]

WPE7206

[0.026825, 0.028448]

[0.016082, 0.017514]

[0.000341, 0.000370]

WPS7403

[0.002477, 0.002716]

[0.026450, 0.027950]

[0.000561, 0.000608]

WPE7604

[0.002478, 0.002716]

[0.020825, 0.022025]

[0.000533, 0.000579]

NPS6801

[0.008977, 0.009663]

[0.024934, 0.026534]

[0.000269, 0.000287]

Mean

[0.016543, 0.017211]

[0.022535, 0.023508]

[0.000458, 0.000484]

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