Identification of Vessel Anomaly Behavior Using Support Vector Machines and Bayesian Networks

Abstract

In this work, a model based on Support Vector Machines (SVMs) classification to identify vessel anomaly behavior has been proposed and implemented. The results are compared to Bayesian Networks (BNs). The real world Automated Identification System (AIS) vessel reporting data is used in this work. The results shows that SVMs can achieve higher accuracy… (More)

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