Research on ship track prediction method based on improved PSO-BP algorithm

FaXin Zhu; JinYuan Li; QinLin Bi; MinLing Lai

doi:10.1117/12.2668566

16 February 2023 Research on ship track prediction method based on improved PSO-BP algorithm

FaXin Zhu, JinYuan Li, QinLin Bi, MinLing Lai

Proceedings Volume 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022); 1259131 (2023) https://doi.org/10.1117/12.2668566
Event: 6th International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 2022, Guangzhou, China

Abstract

Ship track prediction is an important embodiment of ship intellectualization. Aiming at the problems of slow convergence speed and falling into local minimum of standard particle swarm optimization BP network algorithm, an improved PSO-BP neural network algorithm is proposed. The learning rate in BP network changes with the cosine of weight in PSO algorithm. At the same time, PSO algorithm based on sine function change and adaptive change of learning factor is used to optimize the inertia weight. For the original AIS data, layda criterion and cubic spline interpolation were used to remove the outliers and repair the missing values of AIS data. Experimental verification with AIS data after processing shows that the improved PSO-BP algorithm improves the prediction accuracy, the prediction accuracy of latitude and longitude increases by 15.3% and 17.2% respectively, while reducing the possibility of falling into the local minimum and improving the convergence speed.

Citation Download Citation

FaXin Zhu, JinYuan Li, QinLin Bi, and MinLing Lai "Research on ship track prediction method based on improved PSO-BP algorithm", Proc. SPIE 12591, Sixth International Conference on Traffic Engineering and Transportation System (ICTETS 2022), 1259131 (16 February 2023); https://doi.org/10.1117/12.2668566

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