With the increasing of global trade and shipping demand, it is of great significance to promote the improvement of shipping safety. At the present stage, ship collision avoidance system is the weak link of ship’s overall equipment, which also directly affects the navigation safety of ships. In recent years, the international community has paid more and more attention to it. The purpose of this paper is to promote the further improvement of navigation safety through the design and research of ship collision avoidance simulation system based on industrial intelligence. Firstly, the author introduces the relevant concepts and algorithms of artificial intelligence and then, on the basis of the existing research materials, combining with the characteristics of artificial intelligence and the key requirements of ship collision avoidance simulation system, proposes the specific design scheme of the simulation system of ship collision avoidance. The experimental results show that compared with the traditional ship collision avoidance decision system, the response time of the intelligent decision system proposed in this paper is improved by about 27%, the prediction accuracy is improved by about 14%, and the navigation safety of the ship is improved by about 17%. Generally speaking, the simulation system designed in this paper is more scientific, but it needs to be further improved.


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    Titel :

    Design and Research of Ship Collision Avoidance Simulation System Based on Artificial Intelligence


    Weitere Titelangaben:

    Lect. Notes Electrical Eng.


    Beteiligte:
    Chang, Jia-Wei (Herausgeber:in) / Yen, Neil (Herausgeber:in) / Hung, Jason C. (Herausgeber:in) / Wang, Guozheng (Autor:in) / Wang, Yi (Autor:in) / Deng, Hua (Autor:in)

    Kongress:

    International Conference on Frontier Computing ; 2020 ; Singapore, Singapore July 10, 2020 - July 13, 2020


    Erschienen in:

    Frontier Computing ; Kapitel : 119 ; 1047-1054


    Erscheinungsdatum :

    01.01.2022


    Format / Umfang :

    8 pages





    Medientyp :

    Aufsatz/Kapitel (Buch)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch





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