Research Article
Computational Logistics for Container Terminal Handling Systems with Deep Learning
Table 5
Prediction deviation profile of liner berthing time for QRM-LBT-LFI by partial features.
| | Prediction deviation (hours) | Minimum of liners | Maximum of liners | Mean of liners | Median of liners | Mode of liners | SD of liners | Variance of liners | Quantitative proportion of liners (%) |
| | [0, 0.5] | 160.000 | 197.000 | 179.190 | 178.000 | 173.000 | 8.659 | 74.974 | 59.730 | | (0.5, 1] | 58.000 | 76.000 | 67.030 | 68.000 | 68.000 | 4.385 | 19.229 | 22.343 | | (1, 2] | 22.000 | 42.000 | 30.150 | 30.000 | 28.000 | 4.410 | 19.448 | 10.050 | | (2, 3] | 7.000 | 10.000 | 8.630 | 9.000 | 9.000 | 0.702 | 0.493 | 2.877 | | (3, 4] | 6.000 | 7.000 | 6.960 | 7.000 | 7.000 | 0.196 | 0.038 | 2.320 | | (4, 5] | 2.000 | 3.000 | 2.520 | 3.000 | 3.000 | 0.500 | 0.250 | 0.840 | | (5, +∞] | 5.000 | 6.000 | 5.520 | 6.000 | 6.000 | 0.500 | 0.250 | 1.840 |
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