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ASSESSMENT OF THE FUNCTIONAL STATE OF A NETWORK INFRASTRUCTURE OBJECT USING A NEURAL NETWORK APPROACH

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The issues of assessing the functional state of network infrastructure objects are considered, and the need for using alternative assessment methods is justified. Side channels are described, with the use of which it becomes possible to monitor the states of individual objects. The experiment conducted in the framework of the study is described. With the help of two sensors, statistical information about the various operating modes of the network architecture device was read. The obtained data were processed using two-layer direct propagation neural networks with a sigmoidal transfer function in hidden layers. The resulting behavior model of the network infrastructure object can be used as an additional element for determining the functional state.

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