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Automatic Identification System Data Fusion98Marine Research of the National Academy of Marine ResearchDOI: 10.29677/MR.202406_4(1).0006Bengio, Y., Courville, A., & Vincent, P. (2014). Representation Learning: A Review and New Perspectives, (1206.5538). arXiv. https://doi.org/10.48550/arXiv.1206.5538Daranda, A. (2016). Neural Network Approach to Predict Marine Traffic. Baltic Journal of Modern Computing, 4(3), 483-495. https://tinyurl.com/3kavvxnrDogancay, K., Tu, Z., & Ibal, G. (2021). Research into vessel behaviour pattern recognition in the maritime domain: Past, present and future. Digital Signal Processing, 119, 103191. https://doi.org/10.1016/j.dsp.2021.103191Eljabu, L., Etemad, M., & Matwin, S. (2022). Spatial Clustering Method of Historical AIS Data for Maritime Traffic Routes Extraction. 2022 IEEE International Conference on Big Data (Big Data), 893-902. https://doi.org/10.1109/BigData55660.2022.10020646Goerlandt, F., & Kujala, P. (2014). On the reliability and validity of ship%u2013ship collision risk analysis in light of different perspectives on risk. Safety Science, 62, 348-365. https://doi.org/10.1016/j.ssci.2013.09.010Huang, J. C., Nieh, C. Y., & Kuo, H. C. (2019). Risk assessment of ships maneuvering in an approaching channel based on AIS data. Ocean Engineering, 173, 399-414. https://doi.org/10.1016/j.oceaneng.2018.12.058Karata%u015f, G. B., Karagoz, P., & Ayran, O. (2021). Trajectory pattern extraction and anomaly detection for maritime vessels. Internet of Things, 16, 100436. https://doi.org/10.1016/j.iot.2021.100436Liu, T. K., Chen, Y. S., & Chen, Y. T. (2019). Utilization of Vessel Automatic Identification System (AIS) to Estimate the Emission of Air Pollutant from Merchant Vessels in the Port of Kaohsiung. Aerosol and Air Quality Research, 19(10), 2341-2351. https://doi.org/10.4209/aaqr.2019.07.0355Mao, S., Tu, E., Zhang, G., Rachmawati, L., Rajabally, E., & Huang, G. B. (2018). An Automatic Identification System (AIS) Database for Maritime Trajectory Prediction and Data Mining. In J. Cao, E. Cambria, A. Lendasse, Y. Miche, & C. M. Vong (Eds.). Proceedings of ELM-2016, 9, 241-257. Springer International Publishing. https://doi.org/10.1007/978-3-319-57421-9_20Murray, B., & Perera, L. P. (2021). An AIS-based deep learning framework for regional ship behavior prediction. Reliability Engineering & System Safety, 215, 107819. https://doi.org/10.1016/j.ress.2021.107819Nieh, C. Y., Lee, M. C., Huang, J. C., & Kuo, H. C. (2019). RISK ASSESSMENT AND TRAFFIC BEHAVIOUR EVALUATION OF INBOUND SHIPS IN KEELUNG HARBOUR BASED ON AIS DATA. Journal of Marine Science and Technology, 27(4). https://doi.org/10.6119/JMST.201908_27(4).0002Nguyen, D., Vadaine, R., Hajduch, G., Garello, R., & Fablet, R. (2018). A Multi-Task Deep Learning Architecture for Maritime Surveillance Using AIS Data Streams. 2018 IEEE 5th International Conference on Data Science and Advanced Analytics (DSAA), 331-340. https://doi.org/10.1109/DSAA.2018.00044National Academy of Marine Research. (2024). National Ocean Database and Sharing System. https://nodass.namr.gov.tw/dataInfo?metadataid=1REFERENCES