Zavitaev Kirill Vitalievich (Postgraduate student, lecturer of the Department of «Engineering Ecology and Life Safety», FGAOU VO «MSTU «STANKIN»)
Yagolnitzer Olga Vladimirovna (Ph.D. technical. sciences, associate professor of the Department of «Engineering Ecology and Life Safety», FGAOU VO «MSTU «STANKIN»)
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the article is devoted to the topic of regression analysis of Gauss and MRR-2017 models, where the quality assessment of two models was carried out for the predetermined parameters of the technological process, as well as the dependence between the distance from the pollution source and the concentration of nitrogen dioxide was determined. Regression analysis and quality assessment of Gaussian and MRR-2017 models were carried out for two closely located sources of pollution, which are the basis for the diversion of harmful substances formed as a result of fuel combustion in the boilers of the boiler plant. The aim of the work is to determine the strength of the closeness of the relationship between the distance from the pollution source and the concentration of the studied substance, as well as to assess the quality of the most popular models of dispersion of harmful substances as a means of automating the distribution of the content of harmful substances in the surface layer of the atmosphere. Special attention is paid to the comparative analysis of Gaussian and MRR-2017 models using the criteria of coefficient of determination and sum of squares of residuals, the value of which determines the quality of the two studied models for forecasting. Using regression analysis it is possible to determine not only how good a particular model is and can be used by environmental protection agencies, but also to create prerequisites for training and improving new models in environmental protection activities.
Keywords:regression analysis, coefficient of determination, sum of squares of residuals, Gaussian model, MPR-2017, model quality, automation tools.
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Citation link:
Zavitaev K. V., Yagolnitzer O. V. QUALITY ASSESSMENT OF GAUSS AND MRR-2017 MODELS BY APPLYING THE METHOD OF REGRESSION ANALYSIS // Современная наука: актуальные проблемы теории и практики. Серия: Естественные и Технические Науки. -2025. -№06/2. -С. 91-97 DOI 10.37882/2223-2966.2025.06-2.11 |
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