Neural network model for the solution of tasks of technical diagnostics of the transport telecommunication network

The existing systems of monitoring and management of the transport telecommunication network (TTN) managements of separate network elements of a network. Transition to monitoring and management of TTN in general is a complex challenge which is fully not solved by modern control systems of TTN, first of all, because of complexity of identification of a condition of a network in general for the set time interval. The research objective consists in a possibility of the solution of problems of technical diagnosing of TTN in the conditions of large volume of measurements in a set of diagnostic parameters of the TTN elements and limitation of temporary resources on decision-making. For the solution of a goal the following methods were used: theories of counts, system analysis and neural networks. In work the developed neural network model for the solution of problems of technical diagnosing of TTN of big scale which differs from known for a possibility of work with various groups of diagnostic data and allows to consider physical and logical structures of a network is presented. The model allows to refer current state of TTN to one of the entered states.