Recurrent neural networks to analyze the quality of natural gas | Vestnik Tomskogo gosudarstvennogo universiteta. Upravlenie, vychislitelnaja tehnika i informatika – Tomsk State University Journal of Control and Computer Science. 2021. № 55. DOI: 10.17223/19988605/55/2

Recurrent neural networks to analyze the quality of natural gas

Comparative analysis of various neural network models was carried out for natural gas quality analysis. Based on the results of such analysis, it was concluded that recurrent neural networks are main statistical models in this problem. This paper considers a recurrent neural network with a more complex architecture. The neural network with gated recurrent unit is used in the discussed task in particular. The comparison of the main recurrent neural network models (simple recurrent neural network, recurrent neural network with long short-term memory, recurrent neural network with gated recurrent unit) is shown. Models accuracy characteristics are shown for analyzing the models performance.

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Keywords

recurrent neural networks, natural gas quality analysis, gated recurrent unit

Authors

Name	Organization	E-mail
Brokarev Ivan A.	National University of Oil and Gas «Gubkin University»	brokarev.i@gubkin.ru
Farkhadov Mais P.	V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences	mais@ipu.ru
Vaskovskii Sergei V.	V.A. Trapeznikov Institute of Control Sciences of Russian Academy of Sciences	v63v@yandex.ru

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References

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