In order to avoid the phenomenon that the good rock is over-supported and the poor rock is under-supported, based on the XGBoost algorithm combined with the roadway safety factor, an intelligent evaluation and optimization design system of on-demand support in Longqiao Iron Mine was developed. 7 on-demand anchor mesh support indexes and 5 on-demand plain spray support indexes affecting the stability of roadway in Longqiao Iron Mine were used as the main input values. 60 sets of practical roadway data were selected as examples to carry out the on-demand optimization support design and effectiveness evaluation. The results show that at the level of −370.0 m, the surrounding rock grade is better, the safety factor is larger, and the support measures are not needed. At the level of −382.5 m and −395.0 m, the surrounding rock grade is slightly worse, the safety factor is slightly lower, and the plain spray support form is required. At the level of −407.5 m and −420.0 m, the surrounding rock grade is above the third grade, and the surrounding rock properties are poor, so it is necessary to adopt the form of anchor mesh support. The intelligent evaluation and optimization design system of on-demand support provides real-time rock mass quality evaluation and support scheme optimization for Longqiao Iron Mine, which has effectively improved the safety of roadway and significantly saved the support cost.

XGBoost model  /  Safety factor  /  Rock roadway  /  Effectiveness evaluation  /  On-demand support