Research Article
Computational Logistics for Container Terminal Handling Systems with Deep Learning
Table 9
Prediction deviation profile of liner berthing time for QRM-LBT-LFI by complete 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, 0.1] | 6.000 | 294.000 | 214.950 | 237.000 | 288.000 | 80.353 | 6456.548 | 71.650 | | (0.1, 0.2] | 6.000 | 236.000 | 77.4500 | 60.000 | 12.000 | 68.301 | 4664.968 | 25.817 | | (0.2, 0.3] | 0.000 | 100.000 | 7.030 | 1.000 | 0.000 | 16.150 | 260.809 | 2.343 | | (0.3, 0.4] | 0.000 | 14.000 | 0.500 | 0.000 | 0.000 | 2.062 | 4.250 | 0.167 | | (0.4, 0.5] | 0.000 | 6.000 | 0.060 | 0.000 | 0.000 | 0.597 | 0.356 | 0.020 | | (0.5, +∞] | 0.000 | 1.000 | 0.010 | 0.000 | 0.000 | 0.100 | 0.010 | 0.003 |
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