Modeling and forecasting seasonal and cyclical events using retrospective data

Anatoly Darmanyan; Aleksey Rogachev

doi:10.1051/e3sconf/202021706007

All issues

Volume 217 (2020)

E3S Web Conf., 217 (2020) 06007

References

Open Access

Issue		E3S Web Conf. Volume 217, 2020 International Scientific and Practical Conference “Environmental Risks and Safety in Mechanical Engineering” (ERSME-2020)


Article Number		06007
Number of page(s)		6
Section		Digital Technologies for Sustainability
DOI		https://doi.org/10.1051/e3sconf/202021706007
Published online		14 December 2020

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[1] A.A. Khalafyan, Statistica 6, Static data analysis Textbook (Moscow: Binom-Press, 512, 2007) [Google Scholar]

[2] V.P. Borovikov, V.P. Ivchenko, Forecasting in the STATISTICA system in the WINDOWS environment: fundamentals of theory and intensive practice on the computer (Textbook. Moscow: Finance and statistics, 368, 2006) [Google Scholar]

[3] Yu.P. Lukashin, Adaptive methods for short-term time series forecasting (Moscow: Finance and statistics, 368, 2003) [Google Scholar]

[4] A.P. Darmanian, N.M. Veselova, Scientific significance of statistical methods for analysing experimental data in the system of postgraduate agricultural education, Current issues of professional education 3(12), 33-37 (2018) [Google Scholar]

[5] Forecast of world and Russian energy development (Moscow: INEI RAN – Analytical center under the government of the Russian Federation, 2016) [Google Scholar]

[6] S.A. Ayvazyan, Applied statistics, Fundamentals of econometrics 2001 2, 432 (2001) [Google Scholar]

[7] Statistics of the Ministry of energy Retrieved from: https://minenergo.gov.ru/activity/statistic/ [Google Scholar]

[8] A.F. Rogachev, Energy assessment and optimization of programmed agricultural production using retrospective data, E3S Web of Conferences. The conference proceedings Innovative Technologies in Environmental Science and Education. Don State Technical Universyty (2019) [Google Scholar]

[9] K.E. Tokarev et al. IOP Conf. Ser. : Earth Environ. Sci. 488, 012047 (2020) [CrossRef] [Google Scholar]

[10] A.F. Rogachev, Mathematical modeling of economic dynamics in agricultural production: Monograph (Volgograd: Publishing house of Volgograd State University 172, 2014) [Google Scholar]

[11] A.F. Rogachev et al. A set of data on retrospective grain yield for neural network modeling IOP Conf. Ser. : Earth Environ. Sci. 577, 012006 (2020) [Google Scholar]