A CBR-Based Approach for Ship Collision Avoidance

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TypeArticle
ConferenceProceedings of The Twenty First International Conference on Industrial, Engineering & Other Applications of Applied Intelligent Systems (IEA-AIE 2008), June 18-20, 2008., Wroclaw, Poland
Subjectcase-based reasoning; ship collision avoidance; case retrieval; case learning
AbstractIn this paper, we propose a novel CBR-based approach for ship collision avoidance. After the introduction of the CBR-based decision-making support, we present two abstraction principles, selecting view points and describing granularity, to create collision avoidance cases from real-time navigation data. Several issues related case creation and CBR-based decision-making support are discussed in details, including case presentation, case retrieval and case learning. Some experimental results show the usefulness and applicability of CBR-based approach for ship collision avoidance.
Publication date
LanguageEnglish
AffiliationNRC Institute for Information Technology; National Research Council Canada
Peer reviewedNo
NRC number49918
NPARC number8913760
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Record identifierfae33ffb-552b-4187-aa46-d4abe45f2615
Record created2009-04-22
Record modified2016-05-09
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