Prediction of the properties anhydrite construction mixtures based on neural network approach

Y. M. Fedorchuk, N. V. Zamyatin, G. V. Smirnov, O. N. Rusina, M. A. Sadenova

Research output: Contribution to journal › Article

2 Citations (Scopus)

Abstract

The article considered the question of applying the backstop modeling mechanism from the components of anhydride mixtures in the process of managing the technological processes of receiving construction products which based on fluoranhydrite.

Original languageEnglish
Article number012039
JournalJournal of Physics: Conference Series
Volume881
Issue number1
DOIs
Publication statusPublished - 30 Aug 2017
EventInternational Conference on Innovations in Non-Destructive Testing, SibTest 2017 - Sosnovkav, Novosibirsk, Russian Federation
Duration: 27 Jun 2017 → 30 Jun 2017

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anhydrides
products
predictions

ASJC Scopus subject areas

  • Physics and Astronomy(all)

Cite this

Prediction of the properties anhydrite construction mixtures based on neural network approach. / Fedorchuk, Y. M.; Zamyatin, N. V.; Smirnov, G. V.; Rusina, O. N.; Sadenova, M. A.

In: Journal of Physics: Conference Series, Vol. 881, No. 1, 012039, 30.08.2017.

Research output: Contribution to journal › Article

Fedorchuk, YM, Zamyatin, NV, Smirnov, GV, Rusina, ON & Sadenova, MA 2017, 'Prediction of the properties anhydrite construction mixtures based on neural network approach', Journal of Physics: Conference Series, vol. 881, no. 1, 012039. https://doi.org/10.1088/1742-6596/881/1/012039
Fedorchuk YM, Zamyatin NV, Smirnov GV, Rusina ON, Sadenova MA. Prediction of the properties anhydrite construction mixtures based on neural network approach. Journal of Physics: Conference Series. 2017 Aug 30;881(1). 012039. https://doi.org/10.1088/1742-6596/881/1/012039
Fedorchuk, Y. M. ; Zamyatin, N. V. ; Smirnov, G. V. ; Rusina, O. N. ; Sadenova, M. A. / Prediction of the properties anhydrite construction mixtures based on neural network approach. In: Journal of Physics: Conference Series. 2017 ; Vol. 881, No. 1.
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