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• W3111543693 abstract "Ship collision avoidance measures are important for reducing marine accidents caused by human factors and various natural environmental factors and can also prevent property loss and casualties. In recent years, various methods have been used to study collision avoidance, including ship domain models. This paper proposes a ship domain model based on fuzzy logic aimed at providing early warning of ship collision risk and a reasonable reference that can be used in combination with the International Regulation for Preventing Collisions at Sea (COLREGs). The composition fuzzy inference combining more than one fuzzy inference process is first used to introduce as many factors as possible related to ship collision risk for calculating the ship domain. In this way, the calculation of the ship domain size is more accurate, and a more accurate reference can be provided to sailors, which could save both time and labor by reducing errors. A fuzzy inference system based on if-then fuzzy rules was established in MATLAB and simulation experiments were conducted. The simulation results suggest that the proposed method is feasible and can help sailors make subjective decisions to effectively avoid the occurrence of collision accidents." @default.
• W3111543693 created "2020-12-21" @default.
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• W3111543693 date "2020-12-08" @default.
• W3111543693 modified "2023-10-17" @default.
• W3111543693 title "Research on Early Warning of Ship Danger Based on Composition Fuzzy Inference" @default.
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• W3111543693 doi "https://doi.org/10.3390/jmse8121002" @default.
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