Computer Science ›› 2018, Vol. 45 ›› Issue (11A): 126-131.

• Intelligent Computing • Previous Articles     Next Articles

Prediction Model of Ship Trajectory Based on LSTM

QUAN Bo1, YANG Bo-chen2, HU Ke-qi2, GUO Chen-xuan1, LI Qiao-qin2   

  1. Chengdu Spaceon Technology Co.Ltd.,10th Institute of CETC,Chengdu 611731,China1
    School of Information and Software Engineering,University of Electronic Science and Technology,Chengdu 610054,China2
  • Online:2019-02-26 Published:2019-02-26

Abstract: It is imperative to raise the level of decision-making for vessel traffic service (VTS) system in the light of the increasingly complex maritime circumstances.Aiming at the multidimensional characteristics of the ship’s navigation trajectory and the demand for the accuracy and the real-time prediction of the ship’s trajectory,a prediction method combining ship trajectory automatic identification system (AIS) data and deep learning was proposed.The feature expression of vessel behavior based on AIS data was established and the recurrent neural network-long short term memory (RNN-LSTM) model was proposed.The model was trained by AIS data from the Guangzhou Harbor and used to predict vessel trajectory.The results show that the method can predict the characteristics of vessel trajectory timely with acceptable accuracy.Compared with the traditional processing method,it is more superior in processing time series data.

Key words: AIS, LSTM, RNN, Ship trajectory predict

CLC Number: 

  • TP183
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