Research Article
Computational Logistics for Container Terminal Handling Systems with Deep Learning
Table 6
Prediction deviation profile of liner berthing time for QRM-LBT-LTW 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] | 0.000 | 82.000 | 40.550 | 41.500 | 16.000 | 24.026 | 577.248 | 47.151 | | (0.1, 0.2] | 4.000 | 54.000 | 28.740 | 28.000 | 19.000 | 13.197 | 174.172 | 33.419 | | (0.2, 0.3] | 0.000 | 55.000 | 11.970 | 6.000 | 2.000 | 12.467 | 155.429 | 13.919 | | (0.3, 0.4] | 0.000 | 45.000 | 4.060 | 1.000 | 0.000 | 8.335 | 69.476 | 4.721 | | (0.4, 0.5] | 0.000 | 17.000 | 0.580 | 0.000 | 0.000 | 2.426 | 5.884 | 0.674 | | (0.5, +∞] | 0.000 | 3.000 | 0.100 | 0.000 | 0.000 | 0.436 | 0.190 | 0.116 |
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