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

Division for General Technical Subjects

Research output: Contribution to journal › Article › peer-review

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 language	English
Article number	012039
Journal	Journal of Physics: Conference Series
Volume	881
Issue number	1
DOIs	https://doi.org/10.1088/1742-6596/881/1/012039
Publication status	Published - 30 Aug 2017
Event	International Conference on Innovations in Non-Destructive Testing, SibTest 2017 - Sosnovkav, Novosibirsk, Russian Federation Duration: 27 Jun 2017 → 30 Jun 2017

ASJC Scopus subject areas

Physics and Astronomy(all)

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title = "Prediction of the properties anhydrite construction mixtures based on neural network approach",

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.",

author = "Fedorchuk, {Y. M.} and Zamyatin, {N. V.} and Smirnov, {G. V.} and Rusina, {O. N.} and Sadenova, {M. A.}",

year = "2017",

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AU - Smirnov, G. V.

AU - Rusina, O. N.

AU - Sadenova, M. A.

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JO - Journal of Physics: Conference Series

JF - Journal of Physics: Conference Series

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

Abstract

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