Gas stock amount regression analysis based approach to solving the gas balance problem

the technological process of accounting for gas consumption in the gas transmission system is considered in this paper. One of the problems of the metering system is the gas imbalance (imbalance) arising from the influence of many changing quantities, including such as nonlinearly dependent characteristics of the working medium (natural gas), equipment, pipelines, and the environment. One of the components of the imbalance is the amount of gas in the main pipeline, which, among other factors, is influenced by the temperature of the soil at the depth of the gas pipeline, which is updated monthly according to statistical data. The paper proposes an approach to calculating the value of the reserve based on the soil temperature, which is updated daily, and also proposes forecasting the value of the gas reserve in the pipeline using regression analysis; various machine learning methods were used using the Matlab environment, the regression results were compared based on the application of these methods, the most significant parameters in calculating the gas reserve were identified, clustering was applied to determine the sign of the gas reserve in the pipeline. Modern mathematical apparatus and computing facilities can be used for the development of software and with subsequent integration into complex computing systems.

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