Intelligent system of the railway dangerous land control
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Abstract
Topicality. Railway transport is one of the most important objects of critical infrastructure of Ukraine and in order to ensure its safety it is necessary to improve the system of safety management of trains by introducing modern computer information technologies and tools. One of these ways is the use of an intelligent system for monitoring the condition of dangerous sections of the railroad, in particular at railway crossings. The solution to this problem becomes even more urgent in the event that the mobile network is overloaded and the driver loses contact with the video surveillance camera on the move, resulting in the inability to observe the state of migration. The article proposes the use of an intelligent system for monitoring the condition of railway dangerous sections, in particular on the railway crossing. We discuss the description of the work and architecture of convolutional neural networks that are used in this system. Results. The optimized architecture of the neural network is proposed for solving the problem of identifying dangerous situations on the railroad. The recommendations for setting up variable parameters during construction and training of the convolutional neural network are given. The results of testing the work of the network are given when recognizing the free path and in the presence of a critical situation in different conditions. Conclusions. The intelligent system for controlling the state of dangerous sections of the railway has been further developed, which differs from the known use of optimized architecture to reduce the processing time of images, which allowed to improve the accuracy and efficiency of the recognition of situations in the images and, consequently, increase the safety level of rail transport in different dangerous areas.
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References
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