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Pattern Parameterization with Granules in Ship Movements: Describing identifying aspects of movement patterns with varying levels of granularity
University of Skövde, School of Humanities and Informatics.
2010 (English)Independent thesis Basic level (degree of Bachelor), 20 credits / 30 HE creditsStudent thesis
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.

Place, publisher, year, edition, pages
2010. , 27 p.
Keyword [en]
Pattern detection, AIS, ship surveillance, machine learning
National Category
Computer Science
Identifiers
URN: urn:nbn:se:his:diva-4392OAI: oai:DiVA.org:his-4392DiVA: diva2:350360
Uppsok
Technology
Examiners
Available from: 2010-10-11 Created: 2010-09-10 Last updated: 2010-10-11Bibliographically approved

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fulltext(621 kB)4968 downloads
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Type fulltextMimetype application/pdf

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Adolfsson, John
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CiteExportLink to record
Permanent link

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Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf