- Tytuł:
- Optimization of daily operations in the marine industry using ant colony optimization (ACO)-An artificial intelligence (AI) approach
- Autorzy:
-
Sardar, A.
Anantharaman, M.
Garaniya, V.
Khan, F. - Powiązania:
- https://bibliotekanauki.pl/articles/24201433.pdf
- Data publikacji:
- 2023
- Wydawca:
- Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
- Tematy:
-
ant colony optimization
artificial intelligence
maritime transport
International Maritime Organization
international safety management
formal safety assessment
algorithms - Opis:
- The maritime industry plays a crucial role in the global economy, with roughly 90% of world trade being conducted through the use of merchant ships and more than a million seafarers. Despite recent efforts to improve reliability and ship structure, the heavy dependence on human performance has led to a high number of casualties in the industry. Decision errors are the primary cause of maritime accidents, with factors such as lack of situational awareness and attention deficit contributing to these errors. To address this issue, the study proposes an Ant Colony Optimization (ACO) based algorithm to design and validate a verified set of instructions for performing each daily operational task in a standardised manner. This AI-based approach can optimise the path for complex tasks, provide clear and sequential instructions, improve efficiency, and reduce the likelihood of human error by minimising personal preference and false assumptions. The proposed solution can be transformed into a globally accessible, standardised instructions manual, which can significantly contribute to minimising human error during daily operational tasks on ships.
- Źródło:
-
TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2023, 17, 2; 290--295
2083-6473
2083-6481 - Pojawia się w:
- TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
- Dostawca treści:
- Biblioteka Nauki
Artykuł