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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.

Citations

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Details

Category:
Magazine publication
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
Sources of funding:
  • Działalność statusowa
Verification:
Gdańsk University of Technology

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