Keywords and phrases: regression model, nuclear power plants, least squares method.
Received: July 2, 2021; Accepted: August 16, 2021; Published: October 7, 2021
How to cite this article: S. I. Noskov and A. S. Vergasov, Regression model of electricity generation at nuclear power plants in Russia with respect to the nonlinear predictors, Advances and Applications in Statistics 70(2) (2021), 229-233. DOI: 10.17654/AS070020229
This Open Access Article is Licensed under Creative Commons Attribution 4.0 International License
References:
[1] E. A. Debryanskaya and E. A. Yanova, Correlation-regression analysis of performance indicators of nuclear power plants of the Russian federation, Interactive Science 4 (2016), 118-121. [2] E. A. Sushkevich, Models of state support and stimulation of renewable energy development: foreign experience, Topical Issues of Economic Sciences 29(1) (2013), 93-98. [3] O. V. Marchenko and S. V. Solomin, About the methodological approach to development of an agent model of world energy, Science and Modernity 10(2) (2011), 73-77. [4] A. G. Mustafaev, Neural network model for forecasting solar energy level for alternative energy problems, Software Systems and Computational Methods 2 (2016), 150-157. [5] R. A. Golovin, Integrated economic and mathematical model for forecasting the country market of nuclear energy, Energy Reliability and Safety 4(35) (2016), 12-18. [6] V. I. Zykov and D. E. Zhuravlev, Mathematical model of the integrated system for monitoring fire safety of power objects, Fires and Emergencies: Prevention, Elimination 2 (2019), 9-15. [7] S. I. Noskov, A. S. Vergasov, V. O. Zayanchukovskaya and N. I. Gluhov, Interval regression models of a machine-building enterprise, IOP Conference Series: Materials Science and Engineering, Krasnoyarsk Science and Technology City Hall of the Russian Union of Scientific and Engineering Associations, Krasnoyarsk, Russia, 2020, 42026. [8] S. I. Noskov and A. S. Vergasov, Application criterion of displacement when choosing the method of evaluating the parameters of regression equations, Adv. Appl. Stat. 61(1) (2020), 89-94. [9] S. I. Noskov, Method of mixed estimation of linear regression parameters: application features, Bulletin of Voronezh State University Ser.: System Analysis and Information Technologies 1 (2021), 126-132. [10] S. I. Noskov and A. S. Vergasov, Discrete dynamic model of cargo turnover by railway transport, Advances and Applications in Discrete Mathematics 27(1) (2021), 141-146. [11] S. I. Noskov and A. S. Vergasov, Choosing a regression model for the transportation of goods in Russia, Adv. Appl. Stat. 69(1) (2021), 1-5. [12] S. I. Noskov, Construction of a linear regression taking into account expert information relating to the comparative importance of variables, Bulletin of the Technological University 2(24) (2021), 83-86. [13] S. I. Noskov and A. S. Vergasov, Regression model of structural factors of cyber threats, Software Engineering 4(11) (2020), 251-256. [14] A. V. Lakeyev and S. I. Noskov, A description of the set of solutions of a linear equation with intervally defined operator and right-hand side, Doklady RAN, Matematika 330(4) (1993), 430-433. [15] V. B. Golovchenko and S. I. Noskov, Estimation of an econometric model using statistical data and expert information, Automation and Remote Control 4(52) (1991), 542-548. [16] S. I. Noskov, Compromise Pareto’s evaluation of parameters for regression model of damage by cybercrimes, Vestnikkibernetiki 1(41) (2021), 71-75. [17] S. I. Noskov, The criterion of “consistency of behavior” in the regression analysis, Modern Technologies, System Analysis, Modeling 1(37) (2013), 107-110. [18] S. I. Noskov, Parameters estimation of the fitting functions with constant proportions, Modern Technologies, System Analysis, Modeling 2(38) (2013), 135-136. [19] S. I. Noskov, A. P. Khomenko, S. K. Kargapol’tcev, A. V. Daneev and A. V. Lukyanov, Method of point estimation of the Pareto set in linear multicriteria problem, Far East J. Math. Sci. (FJMS) 101(12) (2017), 2803-2809. [20] S. I. Noskov, A. V. Daneev, Yu. N. Alpatov, B. P. Korol’kov, N. P. Dekanova and V. S. Aslamova, Algorithm evaluation of scientific expertise in linear multicriteria problem, Far East J. Math. Sci. (FJMS) 100(12) (2016), 2163-2167.
|