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dc.contributor.authorMurray, Brian
dc.contributor.authorPerera, Lokukaluge Prasad
dc.date.accessioned2021-07-02T11:54:20Z
dc.date.available2021-07-02T11:54:20Z
dc.date.issued2021-05-27
dc.description.abstractThis study presents a deep learning framework to support regional ship behavior prediction using historical AIS data. The framework is meant to aid in proactive collision avoidance, in order to enhance the safety of maritime transportation systems. In this study, it is suggested to decompose the historical ship behavior in a given geographical region into clusters. Each cluster will contain trajectories with similar behavior characteristics. For each unique cluster, the method generates a local model to describe the local behavior in the cluster. In this manner, higher fidelity predictions can be facilitated compared to training a model on all available historical behavior. The study suggests to cluster historical trajectories using a variational recurrent autoencoder and the Hierarchical Density-Based Spatial Clustering of Applications with Noise algorithm. The past behavior of a selected vessel is then classified to the most likely clusters of behavior based on the softmax distribution. Each local model consists of a sequence-to-sequence model with attention. When utilizing the deep learning framework, a user inputs the past trajectory of a selected vessel, and the framework outputs the most likely future trajectories. The model was evaluated using a geographical region as a test case, with successful results.en_US
dc.identifier.citationMurray, Perera. An AIS-based deep learning framework for regional ship behavior prediction. Reliability Engineering & System Safety. 2021en_US
dc.identifier.cristinIDFRIDAID 1912604
dc.identifier.doi10.1016/j.ress.2021.107819
dc.identifier.issn0951-8320
dc.identifier.issn1879-0836
dc.identifier.urihttps://hdl.handle.net/10037/21696
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.journalReliability Engineering & System Safety
dc.rights.accessRightsopenAccessen_US
dc.rights.holderCopyright 2021 The Author(s)en_US
dc.subjectVDP::Technology: 500::Marine technology: 580en_US
dc.subjectVDP::Teknologi: 500::Marin teknologi: 580en_US
dc.titleAn AIS-based deep learning framework for regional ship behavior predictionen_US
dc.type.versionpublishedVersionen_US
dc.typeJournal articleen_US
dc.typeTidsskriftartikkelen_US
dc.typePeer revieweden_US


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