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Publications
Rong, H., Teixeira, A.P. and Guedes Soares, C. (2018), “A model for predicting ship destination routes based on AIS data”, Maritime Transportation and Harvesting of Sea Resources, Guedes Soares, C. & Teixeira A.P. (Eds.), Taylor & Francis Group, London, UK, pp. 257-264
The paper presents a data mining method on Automatic Identification System data. The approach automatically identifies maritime traffic junctions and applies a logistic regression model for predicting the ships’ destination routes based on a set of characteristics of the ships and of their behaviour at a particular junction. In the context of maritime traffic “junction” is a place at which two or more routes diverge. In this area, changes in the course over ground of ships with different final destination routes are consistently observed. The approach consists of detecting turning points based on the Douglas & Peucker algorithm and clustering them based on the density-based spatial clustering of applications with noise algorithm. Then, a multinomial logistic regression model is developed and applied for predicting the most probable destination route of the ships according to their current state in the junction. The proposed method is applied to the southbound traffic leaving the traffic separation scheme off Cape Roca toward the ports of Lisbon, Setubal and Sines.
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