# Trajectory Prediction of Marine Moving Target Using Deep Neural Networks with Trajectory Data
## 8 Future Recommendations  
In future research work, we need to further model optimization and performance enhancement for complex scenarios such as ship steering. We will consider classifying the different navigation patterns of moving targets and separately train track samples of different patterns in order to build precise prediction models. On the other hand, the prediction model can be further improved by incorporating more relevant constraints such as potential navigation areas, geographical conditions, and even meteorology. Conceptualization, X.P. and J.Z. ; methodology, X.Z. and J.Z. ; software, X.Z. and X.W. ; validation, X.W. and X.P. ; formal analysis, X.Z. ; investigation, X.Z. and X.W. ; resources, X.P. and J.Z. ; data curation, X.Z. ; writing--original draft preparation, X.Z. ; writing--review and editing, X.P., J.Z. and X.W. All authors have read and agreed to the published version of the manuscript. This research received no external funding. Not applicable. The data used to support the findings of this study are available from the corresponding author upon request. The authors declare no conflict of interest. * [PERSON] et al. (2019) [PERSON]; [PERSON]; [PERSON] Ship trajectory uncertainty prediction based on a Gaussian Process model. _Ocean Eng._**2019**, _182_, 499-511. [CrossRef]
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