Open Access
Issue
SHS Web Conf.
Volume 107, 2021
9th International Conference on Monitoring, Modeling & Management of Emergent Economy (M3E2 2021)
Article Number 05004
Number of page(s) 7
Section Information Systems and Technologies in Economics
DOI https://doi.org/10.1051/shsconf/202110705004
Published online 24 May 2021
  1. S. Kiyko, Innovative Technologies and Scientific Solutions for Industries 4, 56 (2020) [CrossRef] [Google Scholar]
  2. H.M. Hnatiienko, V.I. Snytiuk, Ekspertni tekhnolohii pryiniattia rishen (Maklaut, Kyiv, 2008) [Google Scholar]
  3. V.M. Molokanova, O.P. Orliuk, V.O. Petrenko, O.B. Butnik-Syverskyi, V.L. Khomenko, Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu 2, 131 (2020) [CrossRef] [Google Scholar]
  4. S.G. Kiyko, Science and technology of the Air Force of the Armed Forces of Ukraine 4, 133 (2020) [Google Scholar]
  5. C.K. Belt, Energy Management for the Metals Industry (CRC Press, New York, 2017) [CrossRef] [Google Scholar]
  6. M. Schulze, H. Nehler, M. Ottosson, P. Thollander, Journal of Cleaner Production 112, 3692 (2016) [CrossRef] [Google Scholar]
  7. M.T. Hagan, H.B. Demuth, M.H. Beale, O.D. Jesús, Neural Network Design, 2nd edn. (2014), ISBN 978-0-9717321-1-7, https://hagan.okstate.edu/NNDesign.pdf [Google Scholar]
  8. P.P. Phyo, C. Jeenanunta, Electricity load forecasting using a deep neural network (2019), https://ph01.tci-thaijo.org/index.php/easr/article/view/116025 [Google Scholar]
  9. D.Y. Goswami, F. Kreith, eds., Energy Eflciency and Renewable Energy Handbook, 2nd edn. (CRC Press, Boca Raton, 2015), ISBN 9780429103070 [CrossRef] [Google Scholar]
  10. C.F. Kutscher, J.B. Milford, F. Kreith, Principles of Sustainable Energy Systems, 3rd edn. (CRC Press, Boca Raton, 2018), ISBN 9780429485589 [Google Scholar]
  11. S. Semerikov, I. Teplytskyi, Y. Yechkalo, A. Kiv, CEUR Workshop Proceedings 2257, 122 (2018) [Google Scholar]
  12. I.M. Kirpichnikova, L.A. Saplin, K.L. Solomakho, Vestnik YuUrGU. Energetika 14, 16 (2014) [Google Scholar]
  13. G.P. Shumilova, N.E. Gotman, T.B. Starczeva, Prognozirovanie elektricheskikh nagruzok pri operativnom upravlenii elektroenergeticheskimi sistemami na osnove nejrosetevykh struktur (URO RAN, Ekaterinburg, 2008) [Google Scholar]
  14. E.V. Bodyanskij, O.G. Rudenko, Iskusstvenny‘e nejronny‘e seti: arkhitektury, obuchenie, primeneniya (Teletekh, Khar‘kov, 2004) [Google Scholar]
  15. V. Derbentsev, A. Matviychuk, N. Datsenko, V. Bezkorovainyi, A. Azaryan, CEUR Workshop Proceedings 2713, 434 (2020) [Google Scholar]
  16. I.V. Brejdo, Y.F. Bulatbaeva, G.D. Orazgaleeva, Algoritm sozdaniya modeli prognozirovaniya energopotrebleniya na osnove nejronnoj seti v Matlab (Novacziya, Krasnodar, 2020) [Google Scholar]
  17. V.V. Vichuzhanin, N.D. Rudnichenko, Informatics and Mathematical Methods in Simulation 6, 333 (2016) [Google Scholar]
  18. Z. Huang, C. Yang, X. Zhou, S. Yang, Cognitive Computation 12, 357 (2020) [Google Scholar]

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