Ship trajectory prediction method and system based on one-dimensional convolutional neural network and LSTM

Abstract

The invention relates to a ship trajectory prediction method based on a one-dimensional convolutional neural network and LSTM. The method comprises the following steps: a data preprocessing step: preprocessing trajectory data including ship position, navigational speed and course information collected by a ship AIS to obtain trajectory segmentation data; a feature extraction step: adopting a one-dimensional convolutional neural network to perform feature extraction optimization on the trajectory segmentation data, and combining the extracted advanced features with the trajectory segmentation data to construct input data of trajectory prediction training; a trajectory prediction model training step: importing the input data into an LSTM neural network model to learn a ship motion law implied in trajectory data; and a trajectory prediction step: predicting the position of the ship at the next moment by using the ship motion law. Compared with other existing prediction methods, the methodhas the advantages of better prediction precision, lower mean square error and quicker prediction.

Description

technical field [0001] The invention belongs to the technical field of intelligent prediction, and in particular relates to a ship trajectory prediction method and system based on a one-dimensional convolutional neural network and LSTM. Background technique [0002] The characteristics of ship navigation and vehicle driving are different, there is no obvious road network constraint, the track is more random, and the prediction is more difficult. The traditional ship trajectory prediction method adopts the method of constructing dynamic equations. This type of method requires professional knowledge support, and needs to be modified according to different ships and scenarios, and the adaptability of the method is poor. The current mainstream method is to use machine learning, which can perform parameter learning based on historical trajectories and current driving trajectories, so that the prediction model has better adaptability. The representative prediction methods based o...

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Problems solved by technology

[0003] In view of the above analysis, the present invention aims to disclose a ship trajectory prediction method and s

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