Identifying the location and size of an underground mine fire with simulated ventilation data and random forest model
- Organization:
- Society for Mining, Metallurgy & Exploration
- Pages:
- 2
- File Size:
- 184 KB
- Publication Date:
- Sep 1, 2023
Abstract
The paper discusses the use of machine learning (ML) to develop a predictive model for determining the location and size of underground mine fires using simulated ventilation data. The study highlights the importance of prompt fire location determination for effective firefighting strategies and reducing injury risks. The ML model was trained with simulated data and achieved an accuracy score of 0.920, which improved to 0.962 by grouping closely connected airways.
Citation
APA: (2023) Identifying the location and size of an underground mine fire with simulated ventilation data and random forest model
MLA: Identifying the location and size of an underground mine fire with simulated ventilation data and random forest model. Society for Mining, Metallurgy & Exploration, 2023.