Using an Artificial Neural Network to Model the Complete Burnout of Mechanoactivated Coal
S. S. Abdurakipov1,2, E. B. Butakov1,2, A. P. Burdukov1, A. V. Kuznetsov1, G. V. Chernova1
1Kutateladze Institute of Thermophysics, Siberian Branch, Russian Academy of Sciences, Novosibirsk, 630090 Russia
2Novosibirsk State University, Novosibirsk, 630090 Russia
Keywords: уголь, высоконапряженное измельчение, синхронный термический анализатор, факел, машинное обучение, искусственная нейронная сеть, coal, high-stress grinding, synchronous thermal analyzer, torch, machine learning, artificial neural network
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%).
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