The article is devoted to research of thermofluctuation processes of insulating materials of power cable lines (SCR) of electric power systems. It was established that an artificial neural network (ANN) can be used to compile a forecast of the temperature regime of a current-carrying core with an accuracy of 2.5% of the actual value of the core temperature. The comparison of the predicted values with the actual ones allows us to talk about the adequacy of the selected network model and its applicability in practice for reliable operation of the cable system of power supply to consumers. The development of an intelligent system for predicting the temperature of the core SCR contributes to the planning of the operating modes of the power grid in order to increase the reliability and energy efficiency of their interaction with the integrated power system.
Keywords: Neural networks, thermofluctuation processes, insulation materials, neural network architecture