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A K-nearest neighbor classifier for ship route prediction

机译:K近邻分类器用于船舶航路预测

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Over the last years the number of AIS messages generated by ships to signal their position has been increasing thus permitting decision support systems to build new strategies based on the elaboration of such data. In this paper we propose an algorithm based on a K-Nearest Neighbor classifier to predict ships routes. The algorithm was tested on real data extracted from AIS messages collected around Malta. Experiments show that our algorithm reaches a precision of 0.794, a recall of 0.785 and an accuracy of 0.931.
机译:在过去的几年中,由船舶发出以发出其位置信号的AIS消息的数量一直在增加,从而使决策支持系统可以根据这些数据的详细说明来制定新的策略。在本文中,我们提出了一种基于K最近邻分类器的算法来预测船舶路线。该算法对从马耳他周围收集的AIS消息中提取的真实数据进行了测试。实验表明,该算法的精度为0.794,召回率为0.785,精度为0.931。

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