A framework of a ship domain-based near-miss detection method using mamdani neuro-fuzzy classification

• Autorzy: Niksa-Rynkiewicz T. , Szlapczynski R.
• Języki publikacji: EN

Abstrakty

EN

Safety analysis of navigation over a given area may cover application of various risk measures for ship collisions. One of them is percentage of the so called near- miss situations (potential collision situations). In this article a method of automatic detection of such situations based on the data from Automatic Identification System (AIS), is proposed. The method utilizes input parameters such as: collision risk measure based on ship’s domain concept, relative speed between ships as well as their course difference. For classification of ships encounters, there is used a neuro-fuzzy network which estimates a degree of collision hazard on the basis of a set of rules. The worked out method makes it possibile to apply an arbitrary ship’s domain as well as to learn the classifier on the basis of opinions of experts interpreting the data from the AIS

• Wydawca: -
• Czasopismo: Polish Maritime Research
• Rocznik: 2018
• Tom: 25
• Numer: Special Issue S1
• Opis fizyczny: p.14-21,fig.,ref.

Twórcy

autor

Niksa-Rynkiewicz T.

• Faculty of Ocean Engineering and Ship Technology, Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland

autor

Szlapczynski R.

• Faculty of Ocean Engineering and Ship Technology, Gdansk University of Technology, 11/12 Narutowicza St., 80-233 Gdansk, Poland

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Identyfikatory

DOI

10.2478/pomr-2018-0017