白响恩,方明权,徐笑锋,肖英杰,吴永明.基于改进LSTM的航运物流路径轨迹修复研究[J].包装工程,2023,44(17):152-159.
BAI Xiang-en,FANG Ming-quan,XU Xiao-feng,XIAO Ying-jie,WU Yong-ming.Ship Logistics Path Trajectory Repair Based on Improved LSTM[J].Packaging Engineering,2023,44(17):152-159. |
| 基于改进LSTM的航运物流路径轨迹修复研究 |
| Ship Logistics Path Trajectory Repair Based on Improved LSTM |
| 投稿时间：2022-11-25 |
| DOI：10.19554/j.cnki.1001-3563.2023.17.018 |
| 中文关键词: 物流路径 货运船舶 AIS轨迹 船舶特性 Bi-LSTM修复 |
| 英文关键词: logistics path cargo ship AIS trajectory ship characteristics Bi-LSTM repair |
| 基金项目:国家自然科学基金面上项目(42176217) |
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| 中文摘要: |
| 目的 提高航运物流路径轨迹信息的挖掘精度和安全效率。方法 对宁波舟山港条帚门水域窄口航道船舶的类型、数量、长度进行统计分析，对货运船AIS物流路径轨迹异常进行识别与修复。考虑船舶实际航行的环境因素，提出一种新的数据纠偏方法。考虑船舶属性与环境因素，以通航宽度和三自由度运动学的转向能力识别异常数据，然后运用Bi-LSTM法对筛选后航运物流路径进行轨迹修复。结果 所提筛选方法不需要轨迹聚类或建立额外的模型进行判别，筛选数据量占总数量的34.26%，修复后的AIS货船物轨迹数据量在原有基础上提升了115.34%。结论 使用文中方法可以有效纠偏和修复异常航运物流路径轨迹数据，为航运物流轨迹数据挖掘提供一定的基础方法。 |
| 英文摘要: |
| The work aims to improve the mining accuracy and safety efficiency of cargo logistics path trajectory information. In this study, the type, quantity and length of ships in the narrow channel of the strip Tiaozhoumen waters of Ningbo Zhoushan Port were statistically analyzed for the identification and repair of AIS logistics path trajectory abnormal points of cargo ships. Considering the environmental factors of actual ship navigation, a new date correction method was proposed. Considering the ship attributes and environmental factors, the abnormal data were identified with the navigation span and steering capability of the three-degree-of-freedom kinematics, and finally the Bi-LSTM method was applied to repair the screened shipping logistics path trajectory. The proposed screening method did not require trajectory clustering or building additional models for discrimination, the screened data accounted for 34.26% of the total quantity, and the repaired AIS cargo ship trajectory data were improved by 115.34% on the original basis. The method can effectively correct and repair abnormal shipping logistics path trajectory data, and provide some basic methods for shipping logistics trajectory data mining. |
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