论文信息 - A model for vessel trajectory prediction based on long short-term memory neural network - 字舞流文

A model for vessel trajectory prediction based on long short-term memory neural network

Each vessel has its own way of sailing in the port region. Any autonomous vessel navigating such a scene should be able to predict the trajectories of surrounding ships and adjust its behaviour to ...

Yong Yin | Huang Tang | Helong Shen | Helong Shen | Yong Yin | Huang Tang

[1] Hassan Ghassemi,et al. Using computational fluid dynamic and artificial neural networks to predict the performance and cavitation volume of a propeller under different geometrical and physical characteristics , 2018 .

[2] Jürgen Schmidhuber,et al. Learning Precise Timing with LSTM Recurrent Networks , 2003, J. Mach. Learn. Res..

[3] Dimitrios Zissis,et al. A cloud based architecture capable of perceiving and predicting multiple vessel behaviour , 2015, Appl. Soft Comput..

[4] Konstantinos Tserpes,et al. Employing traditional machine learning algorithms for big data streams analysis: The case of object trajectory prediction , 2016, J. Syst. Softw..

[5] Piotr Borkowski,et al. The Ship Movement Trajectory Prediction Algorithm Using Navigational Data Fusion , 2017, Sensors.

[6] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.

[7] H. Ghassemi,et al. Performance prediction of hydrofoil- supported catamarans using experiment and ANNs , 2018, Applied Ocean Research.

[8] Seniz Ertugrul,et al. Prediction of manually controlled vessels' position and course navigating in narrow waterways using Artificial Neural Networks , 2009, Appl. Soft Comput..

[9] Hassan Ghassemi,et al. Performance predicting of 2D and 3D submerged hydrofoils using CFD and ANNs , 2017 .