<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>This paper presents a new approach to the existing training of marine control engineering professionals using artificial intelligence. We use optimisation strategies, neural networks and game theory to support optimal, safe ship control by applying the latest scientific achievements to the current process of educating students as future marine officers. Recent advancements in shipbuilding, equipment for robotised ships, the high quality of shipboard game plans, the cost of overhauling, dependability, the fixing of the shipboard equipment and the requesting of the safe shipping and environmental protection, requires constant information on recent equipment and programming for computational intelligence by marine officers. We carry out an analysis to determine which methods of artificial intelligence can allow us to eliminate human subjectivity and uncertainty from real navigational situations involving manoeuvring decisions made by marine officers. Trainees learn by using computer simulation methods to calculate the optimal safe traverse of the ship in the event of a possible collision with other ships, which are mapped using neural networks that take into consideration the subjectivity of the navigator. The game-optimal safe trajectory for the ship also considers the uncertainty in the navigational situation, which is measured in terms of the risk of collision. The use of artificial intelligence methods in the final stage of training on ship automation can improve the practical education of marine officers and allow for safer and more effective ship operation.</p>
</abstract>

This paper presents a new approach to the existing training of marine control engineering professionals using artificial intelligence. We use optimisation strategies, neural networks and game theory to support optimal, safe ship control by applying the latest scientific achievements to the current process of educating students as future marine officers. Recent advancements in shipbuilding, equipment for robotised ships, the high quality of shipboard game plans, the cost of overhauling, dependability, the fixing of the shipboard equipment and the requesting of the safe shipping and environmental protection, requires constant information on recent equipment and programming for computational intelligence by marine officers. We carry out an analysis to determine which methods of artificial intelligence can allow us to eliminate human subjectivity and uncertainty from real navigational situations involving manoeuvring decisions made by marine officers. Trainees learn by using computer simulation methods to calculate the optimal safe traverse of the ship in the event of a possible collision with other ships, which are mapped using neural networks that take into consideration the subjectivity of the navigator. The game-optimal safe trajectory for the ship also considers the uncertainty in the navigational situation, which is measured in terms of the risk of collision. The use of artificial intelligence methods in the final stage of training on ship automation can improve the practical education of marine officers and allow for safer and more effective ship operation.

Computational Intelligence in Marine Control Engineering Education

Polish Maritime Research

This work is licensed under the Creative Commons Attribution 4.0 International License.

{"article-title":"Computational Intelligence in Marine Control Engineering Education"}

This paper presents a new approach to the existing training of marine control engineering professionals using artificial intelligence. We use optimisation...

Computational Intelligence in Marine Control Engineering Education

Online veröffentlicht: 30. Apr. 2021

Seitenbereich: 163 - 172

DOI: https://doi.org/10.2478/pomr-2021-0015

Schlüsselwörter
ship control, marine engineering curriculum, computational intelligence, game theory, computer simulation

© 2021 Józef Lisowski, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Computational Intelligence in Marine Control Engineering Education

Online veröffentlicht: 30. Apr. 2021

Seitenbereich: 163 - 172

DOI: https://doi.org/10.2478/pomr-2021-0015

Schlüsselwörtership control, marine engineering curriculum, computational intelligence, game theory, computer simulation

© 2021 Józef Lisowski, published by Sciendo

This work is licensed under the Creative Commons Attribution 4.0 International License.

Schlüsselwörter
ship control, marine engineering curriculum, computational intelligence, game theory, computer simulation