ISSN (print) 1995-2732
ISSN (online) 2412-9003

 

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Abstract

Problem Statement (Relevance): This article examines contemporary structural models [1] designed for predicting the M25 and М10 coke quality indices, which are used for theoretical research and in practical application by Russia’s coke producers. For the studied models, the model accuracy indicators were brought to a single format and the feagures were compared with the specification given in GOST 5953-93 “+20 mm coke. Physical strength determination” (ISO 556-80). Objectives: The objectives include a comparison and an adequacy analysis of the mathematical models designed for predicting the M25 and M10 coke quality indices based on the models’ predictive accuracy. Methods Applied: The authors carried out a statistical analysis of the confidence intervals for the prediction error of mathematical models designed for predicting the M25 and M10 coke quality indices. The authors looked at the length of the confidence interval at various confidence probabilities before drawing conclusions on the models’ predictive accuracy. Originality: This work provides an opportunity to verify the mathematical models for predicting the M25 and M10 coke quality indices based on the fact that the predictive accuracy of the model should not exceed the allowable discrepancy between two parallels when analyzing the coke quality per GOST 5953. Findings: The article provides a comparison between different structural models in terms of their predictive accuracy. This comparison helped analyze the adequacy of the mathematical models. Practical Relevance: The results obtained can be used for theoretical research and in practical application by Russia’s coke producers.

Keywords

Coke, coke quality indices, mathematical model, classification on the basis of internal structure and algorithm, structural model.

Andrey N. Smirnov – D.Sc. (Physics and Mathematics)

Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. E-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

Danil I. Alekseev – Teaching Assistant

Nosov Magnitogorsk State Technical University, Magnitogorsk, Russia. Е-mail: This email address is being protected from spambots. You need JavaScript enabled to view it.

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