As the global trade grows rapidly and marine resources are increasingly exploited, the ship transport industry has also received attention in the economic development. In the past, the monitoring of ship equipment relied on the daily inspection of the crew and judged whether there was a problem with the equipment through manual experience. This often has a certain risk, because the technical level of the manual, judgment ability, etc., are affected by subjective factors. In the face of the complex and changing Marine environment, manual monitoring is obviously not enough. Therefore, it is necessary to introduce intelligent technology for intelligent monitoring and early warning of ship equipment. The design of this system takes into account that artificial intelligence (AI) can play the role of data analysis and dynamic change analysis in monitoring and early warning. The purpose of this paper is to design a monitoring and early warning system for ship equipment to reflect the status of equipment in real time, issue warnings in time, and avoid some safety risks. This paper mainly uses the investigation method, quantitative analysis method and system test experiment to verify the advantages of AI technology, put forward the advantages and disadvantages of this system, and make improvements. The experimental results show that the neural network has the best prediction ability, with accuracy and prediction ability exceeding 76%.


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    Title :

    Design of Intelligent Ship Equipment Monitoring and Early Warning System Combined with Artificial Intelligence Technology


    Contributors:


    Publication date :

    2024-05-24


    Size :

    5084239 byte




    Type of media :

    Conference paper


    Type of material :

    Electronic Resource


    Language :

    English



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