DEVELOPMENT OF NEURAL NETWORKS FOR PREDICTING THE RISK OF FAILURE OF COMPONENTS OF SHIP MACHINES AND MECHANISMS OF MARINE AUTONOMOUS SURFACE VESSELS
Abstract and keywords
Abstract (English):
The article discusses the possibilities of applying neurocybemetics approaches for the implementation of intelligent prediction of the risk of failure of components of ship technical means of autonomous sea surface ships. In the course of the research, a method was proposed that allows one to build a formal model of the observed units and equipment of ship installations based on the tasks of classification and pattern recognition. An algorithm for the initialization of a neural network is also proposed, which makes it possible to achieve a given accuracy of determining the parameters of the operation of technical means, which makes it possible to provide flexibility in setting up management of emerging risks based on predetermined criteria.

Keywords:
risks, units, equipment, vessel, forecasting, management
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References

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