DEVELOPMENT OF CORRELATION AND REGRESSION MODELS OF ELECTRIC ENERGY INDICATORS OF THE EQUIPMENT WITH CONTINUOUS NATURE OF PRODUCTION

Authors

I.U. Rakhmonov, Tashkent State Technical University
N.N. Niyozov, Tashkent State Technical University
К. Ли, Chungnam National University

Abstract

The article presents an analysis of the use of correlation-regression analysis, which is based on the methods of mathematical statistics and probability theory in the study of the power consumption of enterprises with equipment of continuous production. On the basis of the annual power consumption schedule of the electric steel-smelting shop in a monthly time section, mathematical models have been developed for the power consumption parameters. And also, on the basis of statistical data with the use of a mathematical method, mathematical expressions were obtained for the electric power consumption and the specific consumption for the main equipment of the electric steel-smelting shop. In order to assess the adequacy of the developed mathematical models, mathematical models of the total and specific consumption of their power consumption are compared with actual data. The comparison results show high reliability of the power consumption modes of the main equipment of the facility in question. The analysis of the values of forecast errors with low error rates determines the adequacy of the developed mathematical models of the parameters of power consumption in terms of power consumption and specific consumption for the main equipment of the electric steel-smelting shop. In this regard, they can be used to determine the predicted values of the parameters of power consumption in electric steelmaking equipment.

First Page

203

Last Page

208

References

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Recommended Citation

Rakhmonov, I.U.; Niyozov, N.N.; and Ли, К. (2019) "DEVELOPMENT OF CORRELATION AND REGRESSION MODELS OF ELECTRIC ENERGY INDICATORS OF THE EQUIPMENT WITH CONTINUOUS NATURE OF PRODUCTION," Technical science and innovation: Vol. 2019: Iss. 4, Article 2.
DOI: https://doi.org/10.51346/tstu-01.19.4.-77-0039
Available at: https://btstu.researchcommons.org/journal/vol2019/iss4/2