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

S. S. Abdurakipov; E. B. Butakov; A. P. Burdukov; A. V. Kuznetsov; G. V. Chernova

doi:10.1134/S0010508219060108

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

S. S. Abdurakipov, E. B. Butakov, A. P. Burdukov, A. V. Kuznetsov, G. V. Chernova

Лаборатория моделирования энергетических процессов ФФ

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

2 Цитирования (Scopus)

Аннотация

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%).

Язык оригинала	английский
Страницы (с-по)	697-701
Число страниц	5
Журнал	Combustion, Explosion and Shock Waves
Том	55
Номер выпуска	6
DOI	https://doi.org/10.1134/S0010508219060108
Состояние	Опубликовано - 1 ноя 2019

Доступ к документу

10.1134/S0010508219060108

Другие файлы и ссылки

Link to publication in Scopus

Fingerprint

Подробные сведения о темах исследования «Using an Artificial Neural Network to Simulate the Complete Burnout of Mechanoactivated Coal». Вместе они формируют уникальный семантический отпечаток (fingerprint).

Цитировать

@article{0ceb5968757f4222acbb0fac4b618ddb,

title = "Using an Artificial Neural Network to Simulate the Complete Burnout of Mechanoactivated Coal",

abstract = "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%).",

keywords = "artificial neural network, coal, flame, high-stress pulverization, machine learning, synchronous thermal analyzer",

author = "Abdurakipov, {S. S.} and Butakov, {E. B.} and Burdukov, {A. P.} and Kuznetsov, {A. V.} and Chernova, {G. V.}",

year = "2019",

month = nov,

day = "1",

doi = "10.1134/S0010508219060108",

language = "English",

volume = "55",

pages = "697--701",

journal = "Combustion, Explosion and Shock Waves",

issn = "0010-5082",

publisher = "Springer New York",

number = "6",

}

Using an Artificial Neural Network to Simulate the Complete Burnout of Mechanoactivated Coal. / Abdurakipov, S. S.; Butakov, E. B.; Burdukov, A. P.; Kuznetsov, A. V.; Chernova, G. V.

В: Combustion, Explosion and Shock Waves, Том 55, № 6, 01.11.2019, стр. 697-701.

Результат исследования: Научные публикации в периодических изданиях › статья › рецензирование

TY - JOUR

T1 - Using an Artificial Neural Network to Simulate the Complete Burnout of Mechanoactivated Coal

AU - Abdurakipov, S. S.

AU - Butakov, E. B.

AU - Burdukov, A. P.

AU - Kuznetsov, A. V.

AU - Chernova, G. V.

PY - 2019/11/1

Y1 - 2019/11/1

N2 - 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%).

AB - 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%).

KW - artificial neural network

KW - coal

KW - flame

KW - high-stress pulverization

KW - machine learning

KW - synchronous thermal analyzer

UR - http://www.scopus.com/inward/record.url?scp=85077028056&partnerID=8YFLogxK

U2 - 10.1134/S0010508219060108

DO - 10.1134/S0010508219060108

M3 - Article

AN - SCOPUS:85077028056

VL - 55

SP - 697

EP - 701

JO - Combustion, Explosion and Shock Waves

JF - Combustion, Explosion and Shock Waves

SN - 0010-5082

IS - 6

ER -