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This article is cited in 10 scientific papers (total in 10 papers)
Using an artificial neural network to model the complete burnout of mechanoactivated coal
S. S. Abdurakipovab, E. B. Butakovab, A. P. Burdukova, A. V. Kuznetsova, G. V. Chernovaa a Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090, Russia
b Novosibirsk State University, Novosibirsk, 630090, Russia
Abstract:
An experimental study of the effect of grinding on the thermal destruction of coal is carried out. Artificial neural networks are used to develop a model that allows predicting the degree of burnout of ground coals with high accuracy (an average relative error of 3% and a determination coefficient of 96%).
Keywords:
coal, high-stress grinding, synchronous thermal analyzer, torch, machine learning, artificial neural network.
Received: 19.07.2018 Revised: 22.10.2018 Accepted: 28.11.2018
Citation:
S. S. Abdurakipov, E. B. Butakov, A. P. Burdukov, A. V. Kuznetsov, G. V. Chernova, “Using an artificial neural network to model the complete burnout of mechanoactivated coal”, Fizika Goreniya i Vzryva, 55:6 (2019), 70–75; Combustion, Explosion and Shock Waves, 55:6 (2019), 697–701
Linking options:
https://www.mathnet.ru/eng/fgv635 https://www.mathnet.ru/eng/fgv/v55/i6/p70
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Abstract page: | 33 | Full-text PDF : | 13 |
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