Research Article
Computational Logistics for Container Terminal Handling Systems with Deep Learning
Table 4
Prediction deviation profile of liner berthing time for QRM-LBT-LFO 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] | 108.000 | 134.000 | 126.920 | 128.000 | 129.000 | 4.724 | 22.314 | 60.438 | | (0.5, 1] | 33.000 | 68.000 | 44.110 | 43.000 | 43.000 | 6.107 | 37.298 | 21.005 | | (1, 2] | 15.000 | 25.000 | 18.540 | 18.000 | 18.000 | 1.717 | 2.948 | 8.829 | | (2, 3] | 6.000 | 8.000 | 7.310 | 7.000 | 7.000 | 0.674 | 0.454 | 3.481 | | (3, 4] | 4.000 | 7.000 | 5.660 | 6.000 | 6.000 | 0.533 | 0.284 | 2.695 | | (4, 5] | 2.000 | 4.000 | 3.010 | 3.000 | 3.000 | 0.500 | 0.250 | 1.433 | | (5, +∞] | 4.000 | 5.000 | 4.450 | 4.000 | 4.000 | 0.498 | 0.248 | 2.119 |
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