Research Article
Computational Logistics for Container Terminal Handling Systems with Deep Learning
Table 3
Prediction deviation profile of liner berthing time for QRM-LBT-LTH 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] | 34.000 | 57.000 | 49.620 | 50.000 | 52.000 | 3.638 | 13.236 | 38.465 | | (0.5, 1] | 29.000 | 43.000 | 33.930 | 34.000 | 33.000 | 2.471 | 6.105 | 26.302 | | (1, 2] | 24.000 | 37.000 | 29.430 | 29.000 | 30.000 | 2.543 | 6.465 | 22.814 | | (2, 3] | 5.000 | 8.000 | 5.560 | 5.000 | 5.000 | 0.668 | 0.446 | 4.310 | | (3, 4] | 3.000 | 5.000 | 4.460 | 5.000 | 5.000 | 0.607 | 0.368 | 3.458 | | (4, 5] | 1.000 | 1.000 | 1.000 | 1.000 | 1.000 | 0.000 | 0.000 | 0.775 | | (5, +∞] | 5.000 | 5.000 | 5.000 | 5.000 | 5.000 | 0.000 | 0.000 | 3.876 |
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