## 6 Conclusions  
The occurrence of advanced seismicity and its correlation with the AE activity of coal and rocks under axial loading were analyzed. Building on this analysis, a new statistical method of advanced seismicity for determining the advanced mining influence range was proposed and validated. The main conclusions of this study are as follows. 1. Mining-induced seismicity before the working face is triggered by the instability of coal and rocks under the combined effects of static and dynamic stresses. This seismicity can be used to assess the degree of mining influence on the advanced coal and rock masses and to determine the advanced mining influence range. The stress paths of the advanced coal and rock during coal mining are similar to those of coal and rock samples under axial loading in the lab. The ratios of the AE event number and energy at the active point in the elastic stage to their peak values in lab tests can be used to estimate the ratios of seismic activity at the boundary of the advanced mining influence area to those in the peak stress area. 2. A novel statistical method of the advanced mining-induced seismicity has been proposed to quantitatively assess the advanced mining influence range. First, multiple mining phases within a mining area are selected, and the advanced areas in front of each phase are divided into subareas. The total number and energy of seismic events in each subarea are then calculated and used to plot the total seismic number and total seismic energy curves, with the distances between the midlines of the subareas and the mining phases as the abscissas. Next, the curves from all phases are superimposed and normalized by their respective maximum values. The advanced mining influence range is then determined using thresholds derived from the AE activities of coal and rock samples under axial loading. 3. A case study was conducted using the mining-induced seismicity data from a 1000-m-deep working face in China. Using the novel statistical method, the total seismic event number and total seismic energy curves were plotted and normalized. Thresholds for determining the advanced mining influence ranges were established at 0.076 for the total seismic number and 0.052 for the total seismic energy. The advanced mining influence ranges based on seismic activity were determined to be 275 m for seismic number and 245 m for seismic energy. Additionally, monitoring results from distributed optical fibers in the deep borehole showed an advanced mining influence range of 255 m, which supports the accuracy of the novel statistical method. 4. The novel method is based on the reprocessing of mining-induced seismic data and it is easy to understand and implement. To improve the reliability of the statistical results, the geophone network in the micro-seismic monitoring system should be regularly optimized according to the mining schedule to fully encompass the mining area. Since the seismic number in the working face is more susceptible to variation, it is also acceptable to determine the advanced mining influence range using only the total seismic energy threshold. In the future, based on the findings in this study, the division method and criterion of different dynamic risk areas before the working face will be further studied. A software platform incorporating this method will be developed to process seismic data and display the distribution the advanced dynamic risk areas in real time. This will effectively help to manage and control strong mine pressure and dynamic disasters. Conceptualization, K.Z. and Z.D. ; methodology, K.Z. ; software, K.Z. ; validation, J.K.; formal analysis, J.L. and Z.D. ; investigation, K.Z. and J.K.; resources, K.Z. and L.D. ; data curation, K.Z. ; writing--original draft preparation, K.Z. and J.K.; writing--review and editing, K.Z. and M.D. ; visualization, Z.D. and M.D. ; supervision, P.K. ; project administration, K.Z. and L.D. ; funding acquisition, K.Z. and L.D. All authors have read and agreed to the published version of the manuscript.