Article detail · 2022
Prediction of spontaneous coal combustion tendency using multinomial logistic regression
- Year
- 2022
- Type
- article
Data source split
- YÖKSİS YÖKSİS article record
- YÖKSİS venue International Journal of Occupational Safety and Ergonomics
- Catalog match (ISSN) International Journal of Occupational Safety and Ergonomics
- OpenAlex OpenAlex enrichment (abstract, citations, topics)
Abstract
OpenAlex · English
Spontaneous combustion of coal is a complex underground mining disaster, which mainly threats mine safety and efficiency. Several factors usually cause spontaneous combustion of coal, such as gas concentration, ventilation and coal properties. In this study, spontaneous combustion tendencies of coal mines were predicted considering the effective parameters for an underground coal mine in Turkey. Multinomial logistic regression, a multivariate statistical technique, was applied. Gas concentrations (CH4, CO, O2) and air velocity were defined as factors affecting spontaneous coal combustion. Fire hazard levels of the coal mines were determined as ‘normal situation’ and ‘potential combustion’. It was observed that CH4 and CO variables and CH4 × CO interaction were effective in the formation of clusters. The results indicate that Mine I is more liable to spontaneous combustion than Mine II and Mine III. At the same time, the effects of variations in factors are examined in the study.
Topics
Citations
OpenAlex cited_by_count. Not a WoS or Scopus citation count; those sources have no separate column here.
14 citations
OpenAlex cited_by_count (cache / database)
6 publications in the local catalog that cite this work (OpenAlex reference match; not the full global list).
- Application of Statistical Process Control to Monitor Underground Coal Mine Fires Based on CO Emissions 2024
- Application of Statistical Process Control to Monitor Underground Coal Mine Fires Based on CO Emissions 2024
- Prediction of spontaneous combustion liability for imported steam coals 2025
- Risk Assessment of Coal Dust Explosions in Coal Mines Using a Combined Fuzzy Risk Matrix and Pareto Analysis Approach 2023
- Experimental and machine learning associated study into the spontaneous combustion susceptibility of the steam coals 2026
- Experimental and machine learning associated study into the spontaneous combustion susceptibility of the steam coals 2026