Coal free-swelling index modeling by an ordinal-based soft computing approach

ABSTRACT

Coking coal is the most important reductant agent in the steel-making industry and approximately does not have any substitution. Thus, it is globally still on the list of critical raw materials. The free swelling index (FSI) as a qualitative index is used to assess and rank the coking-ability of coal samples. Although the accurate classification of FSI values is one of the most crucial issues in the coke-making industry, it has become one of the most challenging data-driven problems due to the specific difficulties that lie in coal data characteristics. In this study, by analyzing a robust dataset with over 3600 records from U.S. Geological Survey Coal Quality, an insight was obtained into the FSI classification problem factors that have led to the poor performance of machine learning models. By settling the class imbalance at the data level and applying an efficient model training strategy based on the ordinal classification at the algorithmic level, a novel structure for FSI modeling has been proposed. This study also demonstrates direct relation between the model accuracy and the impact of nonlinear feature selection using Mutual Information instead of traditional linear methods.

KEYWORDS:

• Free swelling index
• coking coal
• ordinal classification
• imbalance learning
• Mutual information

Authors’ Contributions

First Author: Conceptualization, Methodology, Software, Writing - original draft

Second Author: Supervision, Formal analysis, Software

Third Author: Conceptualization, Supervision, Validation, Writing – review & editing

Code Availability

Code available on request from the authors.

Data Availability

Data available on request from the authors.

Disclosure Statement

No potential conflict of interest was reported by the author(s).

Financial/Non-Financial Interests

The authors have no relevant financial or non-financial interests to disclose.

Additional information

Funding

The authors did not receive support from any organization for the submitted work.