Bayesian network modelling of port state control inspections

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dc.contributor.author Μπαστούλης, Αντώνιος el
dc.contributor.author Bastoulis, Antonios en
dc.date.accessioned 2020-11-10T10:13:08Z
dc.date.available 2020-11-10T10:13:08Z
dc.identifier.uri https://dspace.lib.ntua.gr/xmlui/handle/123456789/51869
dc.identifier.uri http://dx.doi.org/10.26240/heal.ntua.19567
dc.description Thesis to obtain the Master Degree inNaval Architecture and OceanEngineering
dc.rights Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 3.0 Ελλάδα *
dc.rights.uri http://creativecommons.org/licenses/by-nc-sa/3.0/gr/ *
dc.subject Port state control en
dc.subject Ship risk profile en
dc.subject Inspection data en
dc.subject Bayesian network en
dc.subject Risk factors en
dc.title Bayesian network modelling of port state control inspections en
heal.type MasterThesis
heal.classification Μαθηματικά el
heal.classification Ρίσκο el
heal.language en
heal.access free
heal.recordProvider ntua el
heal.publicationDate 2019-07-10
heal.abstract The Port State Control (PSC) regimes have been developed after several important maritime accidents allowing countries to inspect foreign-registered ships in port other than those of the flag state and take action against ships that are not in compliance with international rules. In the present research, the risk influencing factors adopted in the definition of the Ship Risk Profile used for selecting ships for inspections under the New Inspection Regime of the Paris Memorandum of Understanding (MoU) on Port the State Control are characterized. Moreover, the PSC inspections at two ports, Thessaloniki and Liverpool ports, are analyzed in terms of type and age of ships and other factors influencing the ships’ risk. In addition, the results of inspections in terms of detentions and number and type of deficiencies found at the two ports are analyzed. Finally, four Bayesian network models are developed using the data from Port State Control inspections. Two models are used to analyze the Thessaloniki port and two models the Liverpool port. The first two Bayesian network models, one for each port, are used to assess how risk factors such as the flag, the age, the recognized organization among others, influence the number of deficiencies and the detention of the ship. The other two models focus on the categories of deficiencies and how the risk factors influence specific deficiencies. en
heal.advisorName Teixeira, Ângelo Manuel Palos
heal.committeeMemberName Teixeira, Ângelo Manuel Palos en
heal.committeeMemberName Antão, Pedro Manuel de Araújo en
heal.committeeMemberName Guedes Soares, Carlos António Pancada en
heal.academicPublisher Σχολή Ναυπηγών Μηχανολόγων Μηχανικών el
heal.academicPublisherID ntua
heal.numberOfPages 94 σ. el
heal.fullTextAvailability false

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Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 3.0 Ελλάδα Except where otherwise noted, this item's license is described as Αναφορά Δημιουργού - Μη Εμπορική Χρήση - Παρόμοια Διανομή 3.0 Ελλάδα