Gas balance control based on a neuro-temporal fuzzy model

Nonlinearity and the number of input factors, the presence of uncertainty in the initial data, can affect, in combination, the gas balance management system’ efficiency in the gas transmission network. This article discusses the use of intelligent methods such as neural networks in the system for accounting for gas consumption in the gas transmission network, fuzzy and temporal logic, in order to maintain a high level of efficiency of its functioning.