Journal of Guangdong University of Technology ›› 2020, Vol. 37 ›› Issue (06): 1-8.doi: 10.12052/gdutxb.200076

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Vessel Traffic Flow Forecast Based on AIS Data of “21st Century Maritime Silk Road”

Li Zhen-fu1, Duan Wei1, Li Zhao-kun2, Deng Zhao1   

  1. 1. School of Transportation Engineering, Dalian Maritime University, Dalian 116026, China;
    2. Shipping Development Research Institute, Dalian Maritime University, Dalian 116026, China
  • Received:2020-06-08 Online:2020-11-02 Published:2020-11-02

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

Key words: AIS (Automatic Identification System) data, time series model, vessel traffic flow

CLC Number: 

  • U692
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