A FRAMEWORK OF A SHIP DOMAIN-BASED NEAR-MISS DETECTION METHOD USING MAMDANI NEURO-FUZZY CLASSIFICATION - Publikacja - MOST Wiedzy

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A FRAMEWORK OF A SHIP DOMAIN-BASED NEAR-MISS DETECTION METHOD USING MAMDANI NEURO-FUZZY CLASSIFICATION

Abstrakt

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.

Tacjana Niksa-Rynkiewicz. (2018). A FRAMEWORK OF A SHIP DOMAIN-BASED NEAR-MISS DETECTION METHOD USING MAMDANI NEURO-FUZZY CLASSIFICATION, 25(S1(97)), 14-21.

Informacje szczegółowe

Kategoria:
Publikacja w czasopiśmie
Typ:
artykuł w czasopiśmie wyróżnionym w JCR
Opublikowano w:
Polish Maritime Research nr 25, wydanie S1(97), strony 14 - 21,
ISSN: 1233-2585
Język:
angielski
Rok wydania:
2018
Opis bibliograficzny:
Niksa-Rynkiewicz T.: A FRAMEWORK OF A SHIP DOMAIN-BASED NEAR-MISS DETECTION METHOD USING MAMDANI NEURO-FUZZY CLASSIFICATION// Polish Maritime Research. -Vol. 25, iss. S1(97) (2018), s.14-21

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