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Pattern Parameterization with Granules in Ship Movements: Describing identifying aspects of movement patterns with varying levels of granularity
Högskolan i Skövde, Institutionen för kommunikation och information.
2010 (engelsk)Independent thesis Basic level (degree of Bachelor), 20 poäng / 30 hpOppgave
Abstract [en]

This report aims to explore a possible transparent alternative to the black box approach of machine learning in identifying a ship’s type from simple movement data, consisting of a set of coordinates with timestamps. This is achieved by an application that converts the set of coordinates to vectors and assigns them various traits, such as turn radius, speed and distance traveled, and then identifying the correlation between collections of different values of these traits, called granules, and different ship types. The results show a definite connection between certain kinds of granules and certain ship types and lay the foundation for building a more well defined syntax for ship identification.

sted, utgiver, år, opplag, sider
2010. , s. 27
Emneord [en]
Pattern detection, AIS, ship surveillance, machine learning
HSV kategori
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URN: urn:nbn:se:his:diva-4392OAI: oai:DiVA.org:his-4392DiVA, id: diva2:350360
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Technology
Examiner
Tilgjengelig fra: 2010-10-11 Laget: 2010-09-10 Sist oppdatert: 2018-01-12bibliografisk kontrollert

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