Performance Prediction and Ratio Design of Coal-Based Solid Waste Cemented Filling Materials Based on Ensemble Learning

Abstract

Coal-based solid wastes, including coal gangue and fly ash, can be extensively utilised in cemented backfill materials. However, the slump, bleeding rate, and mechanical strength of these materials depend nonlinearly on the mixture composition, particle size, solids concentration, and curing conditions, complicating the multi-performance mixture design. This study developed an ensemble-learning framework for the target-specific performance prediction and empirical-uncertainty-aware inverse design of coal-based solid-waste cemented backfill materials. A literature-derived database containing 720 observations and 11 predictors was established. After the target-specific filtering of missing responses, 214 observations were available for the slump, 284 for the bleeding rate, and 711 for the uniaxial compressive strength (UCS). Support vector regression (SVR), Bagging-SVR, AdaBoost-SVR, and Stacking-SVR were evaluated using 20 repeated random 80:20 holdout partitions to assess the within-database predictive performance. Bagging-SVR achieved the lowest mean inner-cross-validation RMSE for all three responses. Its mean test R2 values were 0.969, 0.871, and 0.965 for the slump, bleeding rate, and UCS, respectively, with corresponding RMSE values of 2.228 cm, 1.206 percentage points, and 1.575 MPa. SHAP analysis showed that the coal-gangue particle size and solids concentration received the largest model attributions for the slump and bleeding-rate predictions, whereas the cement content and curing time received the largest attributions for the UCS prediction. The selected Bagging-SVR models were subsequently coupled with multi-objective differential evolution incorporating empirical prediction bounds, component mass balance, and target-specific five-nearest-neighbour applicability-domain constraints. The selected compromise candidate had a solids concentration of 79.46% and coal-gangue, fly-ash, and cement dry-solid mass fractions of 63.29%, 24.95%, and 11.76%, respectively. Its predicted slump, bleeding rate, and 28 d UCS were 21.19 cm, 1.85%, and 6.36 MPa, respectively. The nominal empirical upper bound of the bleeding rate was 3.83%, and the lower bound of the UCS was 3.74 MPa, both satisfying their prescribed limits. However, the nominal slump interval of 15.70–26.65 cm was not fully contained within the prescribed range of 18–26 cm.