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

摘要：

A BP artificial neural network model was established to optimize the final slope angle of open-pit mine, which was based on its powerful selflearning, 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.

关键词： artificial neural network BP model open pitmine slope stability

作者: Fang-wei HE Ming ZHU Wensheng LIU Tie-liang LIU Lianhai WANG

作者单位: College of Resource and Environment,Mining & Safety Technology Key Lab of Hebei Province Hebei Polyt College of Resource and Environment, Mining & Safety Technology Key Lab of Hebei Province Hebei Poly Tangshan Sanyou Mine Corporation Tangshan 063101, Hebei, China

会议类型: 国际会议

会议名称: 2010 International Symposium on Computational Intelligence and Edsign(第三届计算智能与设计国际学术研讨会 ISCID 2010)

会议地点: 杭州

会议语种:英文

页码: 56-59

在线出版日期: 2010-10-29（万方平台首次上网日期，不代表论文的发表时间）