基于“21世纪海上丝绸之路”AIS数据的船舶交通流预测

李振福; 段伟; 李肇坤; 邓昭

doi:10.12052/gdutxb.200076

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基于“21世纪海上丝绸之路”AIS数据的船舶交通流预测

更新时间：2026-05-27

- 基于“21世纪海上丝绸之路”AIS数据的船舶交通流预测
- Vessel Traffic Flow Forecast Based on AIS Data of “21st Century Maritime Silk Road”
- 广东工业大学学报 2020年37卷第6期页码：1-8
- 作者机构：
  
  1. 大连海事大学交通运输工程学院,辽宁,大连,116026
  2. 大连海事大学航运发展研究院,辽宁,大连,116026
- 作者简介：
  
  李振福(1969–)，男，教授，博士，博士生导师，主要从事北极航线规划研究，E-mail：lizhenfu863@163.com
  段伟(1991–)，男，博士研究生，主要研究方向为交通运输规划与管理、复杂网络，E-mail：duanwei106@aliyun.com
- 基金信息：
  
  国家重点研发计划项目(2017YFC1405600);大连海事大学重点科研培育项目(3132019307)
- DOI：10.12052/gdutxb.200076
  中图分类号： U692
- 纸质出版：2020
- 稿件说明：
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李振福, 段伟, 李肇坤, 邓昭. 基于“21世纪海上丝绸之路”AIS数据的船舶交通流预测[J]. 广东工业大学学报, 2020, 37(6): 1-8.

Li Zhen-fu, Duan Wei, Li Zhao-kun, et al. Vessel Traffic Flow Forecast Based on AIS Data of “21st Century Maritime Silk Road”[J]. 2020, 37(6): 1-8.
李振福, 段伟, 李肇坤, 邓昭. 基于“21世纪海上丝绸之路”AIS数据的船舶交通流预测[J]. 广东工业大学学报, 2020, 37(6): 1-8. DOI： 10.12052/gdutxb.200076.

Li Zhen-fu, Duan Wei, Li Zhao-kun, et al. Vessel Traffic Flow Forecast Based on AIS Data of “21st Century Maritime Silk Road”[J]. 2020, 37(6): 1-8. DOI： 10.12052/gdutxb.200076.

摘要

为探究“21世纪海上丝绸之路”船舶交通流规律

基于2018年“21世纪海上丝绸之路”AIS(Automatic Identification System，船舶自动识别系统)数据

利用时间序列模型分别对货船、油轮和货船−油轮这3种情形下的船舶交通流进行了研究。结果显示，船舶交通流变化规律可以用ARIMA模型(Auto-regressive Intergrated Moving Average Model，即差分自回归移动平均模型)，拟合并预测; 货船、油轮和货船−油轮这3种情形有相同的最优选择模型ARIMA(1

2)。“21世纪海上丝绸之路”船舶交通流可由前两个时间周期内的交通流数据拟合预测

并且ARIMA(1

2)模型对单一船型交通流的预测效果优于对混合船型交通流的预测。

Abstract

This paper aims to explore the law of vessel traffic flow on the “21st Century Maritime Silk Road”. Based on the Automatic Identification System data of the “21st Century Maritime Silk Road” in 2018

the time series model is used to analyze the vessel traffic flow of three situations of cargo ships

tankers and cargo ships-tankers. The research shows that: 1) The changes in vessel traffic flow can be fitted and predicted by using the differential autoregressive moving average model (ARIMA). 2) Three situations have the same optimal selection model ARIMA (1

2). The results show that the current vessel traffic flow of “21st Century Maritime Silk Road” can be predicted by the traffic flow in the last two time periods. Three situations all have relatively accurate prediction results

and the prediction effect of the ARIMA (1

2) model on the single ship traffic flow is better than that of the mixed ship traffic flow.

关键词

Keywords

references

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