Decision of Optimum Open-Pit Slope Angle Based on Artifical Neural Network

A BP artificial neural network model was established to optimize the final slope angle of open-pit mine, which was based on its powerful self-learning, nonlinear processing capabilities and advantages of simulation for the slope stability with nonlinear relationship among the parameters. The consideration of effect on the stability of the slope includes Protodrakonov scale of hardness, dip angle of rock stratum, development degree of joint crevice, average annual rainfall, mining depth and final slope angle. The network topology structure of 5-11-1 was built, and the accuracy of the simulation result is above 92 percent. The results show that the specific structure of BP networks can better optimize the final pit slope angle and meet the precision requirement of mining project, which provides a unique advantage of systems analysis in the field of geotechnical engineering application.