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

• Autorzy: Niksa-Rynkiewicz T. , Szłapczyński R.

Identyfikatory

DOI

10.2478/pomr-2018-0017

• 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.

Słowa kluczowe

EN

near-miss; collision risk; ship domain; fuzzy classification

• Wydawca: Gdańsk University of Technology, Faculty of Ocean Engineering & Ship Technology
• Czasopismo: Polish Maritime Research
• Rocznik: 2018
• Tom: S 1
• Strony: 14--21
• Opis fizyczny: Bibliogr. 25 poz., rys., tab.

Twórcy

autor

Niksa-Rynkiewicz T.

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

autor

Szłapczyński R.

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

Bibliografia

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Uwagi

Opracowanie rekordu w ramach umowy 509/P-DUN/2018 ze środków MNiSW przeznaczonych na działalność upowszechniającą naukę (2019).