Research Article
A GIS-Based Spatial-Temporal Autoregressive Model for Forecasting Marine Traffic Volume of a Shipping Network
Table 1
Monthly voyage time-series statistics for ports in the shipping network.
| Rank | Name | Numb | Mean | STDEV | Skewed | Kurtosis |
| 1 | Tainan | 72 | 782.6250 | 91.4560 | 18.8483 | −3.7311 | 2 | Balikpapan | 72 | 42.8472 | 19.2475 | −0.0837 | −1.0373 | 3 | Bangkok | 72 | 469.6388 | 131.894 | 2.7460 | −1.8795 | | | | | | | | 28 | Fangchenggang | 72 | 533.2916 | 119.1145 | 1.0687 | −1.0374 | 29 | Manila | 72 | 254.7222 | 78.7479 | 0.6890 | −0.1742 | 30 | Beihai | 72 | 142.7361 | 55.6224 | 0.3134 | 0.4706 | | | | | | | | 58 | Zhanjiang | 72 | 301.4583 | 76.5235 | 0.9795 | 0.0841 | 59 | Lungsod ng Cebu | 72 | 112.2083 | 62.2414 | −1.0059 | 0.4421 | 60 | Samarinda | 72 | 93.9583 | 57.6522 | −1.3028 | −0.6015 |
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