Vessel Behavior Prediction Based on Improved BP Neural Network

Abstract

In view of the BP (Back Propagation) neural network is easy to fall into local optimization, particle swarm optimization (PSO) algorithm is used to optimize the BP neural network prediction model is proposed. The latitude, longitude, course and speed of the vessel in the AIS are selected as the characteristic parameters of the ship's navigation behavior, data at three consecutive times are input to the network, and the next data is output to train the network. The AIS data in the waters near Laotieshan are selected to verify the effectiveness and the capability of the proposed method. Comparing the prediction results of BP neural network, PSO-BP neural network, the results show that the PSO-BP neural network can jump out of the local optimal solution, and the prediction accuracy is higher.