Olimpiev Sergey Aleksandrovich (Postgraduate student of the department of automated systems
thermal process control
Institute of Thermal and Nuclear Power Engineering
)
Neklyudov Alexey Vasilyevich (Associate professor of the department of automated systems
thermal process control
Institute of Thermal and Nuclear Power Engineering
National Research University
Moscow Power Engineering Institute
)
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Improving the accuracy of modeling the dynamic characteristics of TPP process equipment is an important scientific and technical task. The research is aimed at developing and comparing the classical linear regression model and the combined linear regression model with the addition of an autoregressive element to take into account the time dependence of data and improve the accuracy of forecasting. Methods: The linear regression model is used as a basic method. To account for autocorrelation of the investigated characteristic of the TPP element, an autoregression element based on the use of the residual error of the linear regression model is introduced. Results: The study demonstrates a significant improvement in modeling accuracy after the introduction of the autoregressive element. Conclusions of the study: An approach based on the application of an autoregressive element in a linear regression model is proposed. The obtained results of the study can be applied in the works devoted to the energy field and specific studies of the problems of incorrect characteristics of TPP equipment.
Keywords:machine learning, regression analysis, AR-models, autoregression, equipment characteristics, thermal power plant
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Citation link:
Olimpiev S. A., Neklyudov A. V. APPLICATION OF AR-ELEMENT IN LINEAR MODELS TO ANALYZE CHARACTERISTICS OF THERMAL POWER PLANT ELEMENTS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№04. -С. 126-132 DOI 10.37882/2223-2966.2025.04.31 |
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