Zobrazeno 1 - 6
of 6
pro vyhledávání: '"Alina I. Stepanova"'
Publikováno v:
Algorithms, Vol 17, Iss 10, p 447 (2024)
Currently, machine learning methods are widely applied in the power industry to solve various tasks, including short-term power consumption forecasting. However, the lack of interpretability of machine learning methods can lead to their incorrect use
Externí odkaz:
https://doaj.org/article/f7e7128299e841ae96fb7dc8ad5c7f1d
Publikováno v:
Algorithms, Vol 17, Iss 4, p 150 (2024)
Forecasting the generation of solar power plants (SPPs) requires taking into account meteorological parameters that influence the difference between the solar irradiance at the top of the atmosphere calculated with high accuracy and the solar irradia
Externí odkaz:
https://doaj.org/article/c0d8e6c3b40342939d2d22484e95116b
Publikováno v:
Mathematics, Vol 11, Iss 6, p 1315 (2023)
Digital twin is one of the emerging technologies for the digital transformation of the power industry. Many existing studies claim that the widespread application of digital twins will shift the industry to a principally new level of development. Thi
Externí odkaz:
https://doaj.org/article/69f93dd82dce4f468ff3748f84e0dfde
Autor:
Stepanova, Alina I.1 (AUTHOR) a.i.stepanova@urfu.ru, Khalyasmaa, Alexandra I.1 (AUTHOR), Matrenin, Pavel V.1 (AUTHOR) p.v.matrenin@urfu.ru, Eroshenko, Stanislav A.1 (AUTHOR)
Publikováno v:
Algorithms. Oct2024, Vol. 17 Issue 10, p447. 25p.
Autor:
Matrenin, Pavel V.1,2 (AUTHOR) a.i.khaliasmaa@urfu.ru, Gamaley, Valeriy V.2 (AUTHOR), Khalyasmaa, Alexandra I.1 (AUTHOR) a.i.stepanova@urfu.me, Stepanova, Alina I.1 (AUTHOR)
Publikováno v:
Algorithms. Apr2024, Vol. 17 Issue 4, p150. 20p.
Autor:
Khalyasmaa, Alexandra I.1 (AUTHOR) a.i.khaliasmaa@urfu.ru, Stepanova, Alina I.1 (AUTHOR), Eroshenko, Stanislav A.1 (AUTHOR), Matrenin, Pavel V.1 (AUTHOR)
Publikováno v:
Mathematics (2227-7390). Mar2023, Vol. 11 Issue 6, p1315. 23p.