The development of the Internet, the constantly growing number of network users, and their mutual exchange of information is becoming an important communication bridge. However, this causes a series of technical difficulties, one of which is the growing requirements to network and server equipment and its maintenance. Therefore, the purpose of this study is to develop a computer program for teaching a neural network based on a computer network traffic table. A set of methods was used to achieve the set goal, including analysis, deterministic chaos, and systematization. The study used such software packages as TISEAN, MatLab, NetEmul, and Excel. The study generalized the experience that was relevant to the problem at hand. The study calculated the Lyapunov exponent, which characterizes the presence of chaos in the system. Analysis of the Lyapunov exponent enables using nonlinear dynamics methods to study the nature of the incoming and outbound traffic. With the help of the developed program, the neural network router is capable of prediction short-term parameters of a computer network; this information is sent to the system administrator, which will allow adapting the router to the estimated changes in the computer network.
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