Neural-Network Model for Predicting the Yield of Coking Products


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Abstract

Mathematical analysis of experimental data regarding the quality of coal and coal concentrates and the yield of coking products provides the basis for neural-network models capable of predicting product yields. Such predictions will ultimately be used to optimize coking batches in production conditions.

About the authors

E. V. Vasileva

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: kleossa@yandex.ru
Russian Federation, Kemerovo

V. S. Doroganov

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: DoroganovV@mail.ru
Russian Federation, Kemerovo

A. B. Piletskaya

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: piletsana@gmail.com
Russian Federation, Kemerovo

T. G. Cherkasova

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: ctg.htnv@kuzstu.ru
Russian Federation, Kemerovo

A. G. Pimonov

Gorbachev Kuznetsk Basin State Technical University

Email: kea2949@mail.ru
Russian Federation, Kemerovo

N. G. Kolmakov

PAO Koks

Email: kea2949@mail.ru
Russian Federation, Kemerovo

S. P. Subbotin

Gorbachev Kuznetsk Basin State Technical University; PAO Koks

Author for correspondence.
Email: sybbotin@mail.ru
Russian Federation, Kemerovo; Kemerovo

A. V. Nevedrov

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: nevedrov1978@rambler.ru
Russian Federation, Kemerovo

A. V. Papin

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: papinandrey@rambler.ru
Russian Federation, Kemerovo

E. A. Koshelev

Gorbachev Kuznetsk Basin State Technical University

Author for correspondence.
Email: kea2949@mail.ru
Russian Federation, Kemerovo

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