Risk analysis and prediction of out-of-seam dilution in longwall mining

Abstract

A rock engineering systems (RES) based model is defined to predict the level of risk due to out-of-seam dilution (OSD) in longwall faces. Also, based on the level of risks obtained, a predictive model for the OSD is proposed. Furthermore, an artificial neural networks (ANN) model is developed to predict the OSD. The data collected from thirty-five longwall faces are used to carry out the risk analysis and to develop the predictive models. The results obtained show that the level of risk achieved for each face is in consistence with the corresponding OSD calculated. Also, coefficient of determination (R2) and root mean square error (RMSE) for the ANN model (R2=0.98, RMSE=1.24) and the RES-based model (R2=0.86, RMSE=3.74) have been obtained. These show the good performances of both models. However, the ANN model has a better performance than the RES-based model.