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A Framework of A Ship Domain-Based Near-Miss Detection Method Using Mamdani Neuro-Fuzzy Classification
Abstract
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.
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
-
Polish Maritime Research
no. 25,
edition S1(97),
pages 14 - 21,
ISSN: 1233-2585 - Language:
- English
- Publication year:
- 2018
- Bibliographic description:
- Niksa-Rynkiewicz T., Szłapczyński R.: 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
- DOI:
- Digital Object Identifier (open in new tab) 10.2478/pomr-2018-0017
- Bibliography: test
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- CONTACT WITH THE AUTHORS Rafał Szłapczyński e-mail: rafal@pg.edu.pl open in new tab
- Tacjana Niksa-Rynkiewicz e-mail: tacniksa@pg.edu.pl open in new tab
- Gdansk University of Technology Faculty of Ocean Engineering and Ship Technology 11/12 Narutowicza St. 80 -233 Gdańsk Poland open in new tab
- Sources of funding:
-
- Statutory activity/subsidy
- Verified by:
- Gdańsk University of Technology
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