ABSTRACTS OF ARTICLES OF THE JOURNAL "INFORMATION TECHNOLOGIES".
No. 10. Vol. 27. 2021

DOI: 10.17587/it.27.550-560

K. V. Danilov^{1, 2}, Lead Data Scientist, danilovkostya@yandex.ru, S. V. Maltseva¹, Dr. of Tech., Professor, smaltseva@hse.ru,
¹ National Research University Higher School of Economics, Moscow,101000, Russian Federation,
² PJSC NLMK, Moscow, 119017, Russian Federation

Automated Feature Engineering Method in the Problem of Forecasting Energy Consumption

The automated feature engineering method in the problem of forecasting energy consumption is considered. The algorithm of the method and the scheme of the forecasting model construction are stated. The proposed approach was tested on data about electricity consumption in Russian regions. The results of the computational experiments carried out using the described method demonstrate an increase in the efficiency of the developed forecasting model and improvement of accuracy.
Keywords: automated machine learning, automated feature engineering, forecasting energy consumption, Bayesian optimization

P. 550–560

Acknowledgements: The work was supported by the grant of the Russian Foundation for Basic Research 20-07-00651 A "Study of the stability of distributed decentralized digital systems based on models of the dynamics of social networks".

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