Coal properties can be effectively predicted from scattering spectra using advanced machine learning techniques, improving resource assessment.
The machine learning models demonstrated predictive accuracy, with notable performance differences based on the X-ray source used, impacting coal analysis outcomes.
Assessment utilizing varying X-ray sources allows for deeper insights into coal properties, offering potential improvements in predictive modeling accuracy.
These findings highlight the significance of optimizing X-ray sources, suggesting enhanced methods for coal characterization and exploration.