Vessel Trajectory Prediction Method Based on LSTM Model

The shipping industry serves as a crucial pillar of the global economy. In addressing the economic impacts of shipping accidents, this paper delves into the significance of vessel trajectory prediction technology. Various prediction models are meticulously explored, including models based on neural networks and the differential evolution algorithm-support vector machine. Ultimately, this paper proposes a single-step prediction model based on Long Short-Term Memory (LSTM) networks. Through the elucidation of model concepts, establishment procedures, and empirical analysis, the paper demonstrates the favorable performance of the LSTM model in trajectory prediction. Finally, the article highlights the strengths and weaknesses of the model and suggests directions for improvement. This research can provide the shipping industry with reliable trajectory prediction technology and decision support, advancing the development and application of vessel trajectory prediction technology and providing a reference for further research in the field.