Rockburst criterion based on artificial neural networks and nonlinear regression

Rockburst criterion was studied based on artificial neural networks and nonlinear regression,Firstly the original sample was quantified by artificial neural networks,and then the nonlinear regression method was used to analyze the quantitative sample data.Finally,the new rockburst criterion was obtained.The results show that the new rockbust criterion has a higher predictive precision.