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Detection of vessel...
Detection of vessel anomalies : A Bayesian network approach
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- Johansson, Fredrik (författare)
- Högskolan i Skövde,Institutionen för kommunikation och information,Forskningscentrum för Informationsteknologi,Skövde Artificial Intelligence Lab (SAIL)
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- Falkman, Göran, 1968- (författare)
- Högskolan i Skövde,Forskningscentrum för Informationsteknologi,Institutionen för kommunikation och information,Skövde Artificial Intelligence Lab (SAIL)
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(creator_code:org_t)
- IEEE Computer Society, 2007
- 2007
- Engelska.
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Ingår i: Proceedings of the 2007 International Conference on Intelligent Sensors, Sensor Networks and Information Processing (ISSNIP 2007). - : IEEE Computer Society. - 1424415020 - 9781424415021 - 9781424415014 ; , s. 395-400
- Relaterad länk:
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https://urn.kb.se/re...
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https://doi.org/10.1...
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Abstract
Ämnesord
Stäng
- In this paper we describe a data mining approach for detection of anomalous vessel behaviour. The suggested approach is based on Bayesian networks which have two important advantages compared to opaque machine learning techniques such as neural networks: (1) possibility to easily include expert knowledge into the model, and (2) possibility for humans to understand and interpret the learned model. Our approach is implemented and tested on synthetic data, where initial results show that it can be used for detection of single-object anomalies such as speeding.
Ämnesord
- NATURVETENSKAP -- Data- och informationsvetenskap -- Datavetenskap (hsv//swe)
- NATURAL SCIENCES -- Computer and Information Sciences -- Computer Sciences (hsv//eng)
Nyckelord
- Computer science
- Datavetenskap
- Teknik
- Technology
Publikations- och innehållstyp
- ref (ämneskategori)
- kon (ämneskategori)
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