Gazya Gennady Vladimirovich (PhD in Biology,
Associate Professor of the Higher School of Oil and Gas Technologies and Electric Power Engineering of the Industrial Institute – Branch
of Ugra State University,
Nefteyugansk, Russian Federation
)
Kukhareva Alesya Yuryevna (graduate student,
Surgut State University,
Surgut, Russian Federation
)
Gazya Natalia Fedorovna (graduate student,
Surgut State University,
Surgut, Russian Federation
)
Kozhederov Alexander Igorevich (Senior Lecturer at the Higher School of Oil and Gas Technologies and Electric Power Engineering of the Industrial Institute - Branch
of Ugra State University,
Nefteyugansk, Russian Federation
)
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The authors considered the possibility of using new modes of artificial neural networks when studying the parameters of heart rate variability in male gas processing plant workers working in harmful working conditions and in the process of adapting to factors of the production environment and labor process. Preliminary (in chaos and reverberation mode) tuning of artificial neural networks, taking into account the available set and type of data, made it possible to identify a significant diagnostic sign in men exposed to chronic exposure to harmful production factors using the software product. It was a generalized parameter of the parasympathetic neurovegetative system.
Keywords:new artificial neural networks, heart rate parameters, diagnostic features, industrial ecology.
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Read the full article …
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Citation link:
Gazya G. V., Kukhareva A. Y., Gazya N. F., Kozhederov A. I. APPLICATION OF NEW ARTIFICIAL NEURAL NETWORKS IN INDUSTRIAL ECOLOGY // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№01/2. -С. 10-13 DOI 10.37882/2223-2966.2025.01-2.07 |
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