Using an Artificial Neural Network to Simulate the Complete Burnout of Mechanoactivated Coal

An experimental study of the effect of pulverization 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 pulverized coals with high accuracy (an average relative error of 3% and a determination coef...

Full description

Saved in:
Bibliographic Details
Published inCombustion, explosion, and shock waves Vol. 55; no. 6; pp. 697 - 701
Main Authors Abdurakipov, S. S., Butakov, E. B., Burdukov, A. P., Kuznetsov, A. V., Chernova, G. V.
Format Journal Article
LanguageEnglish
Published Moscow Pleiades Publishing 01.11.2019
Springer Nature B.V
Subjects
Artificial neural networks
Classical and Continuum Physics
Classical Mechanics
Computer simulation
Control
Dynamical Systems
Engineering
Neural networks
Physical Chemistry
Physics
Physics and Astronomy
Vibration
artificial neural network
coal
synchronous thermal analyzer
high-stress pulverization
flame
machine learning
Online AccessGet full text

Cover

More Information
Summary:An experimental study of the effect of pulverization 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 pulverized coals with high accuracy (an average relative error of 3% and a determination coefficient of 96%).
ISSN:0010-5082
1573-8345
DOI:10.1134/S0010508219060108