Affiliations: [a] School of Resources and Civil Engineering, Northeastern University, Shenyang, China
| [b] School of Architecture and Civil Engineering, Shenyang University, Shenyang, China
| [c] Department of Art Design, Shenyang Urban Construction University, Shenyang, China
| [d]
Blekinge Institute of Technology
Correspondence:
[*]
Corresponding author. Zhenyu Liang, School of Resources and Civil Engineering, Northeastern University, Shenyang, 110819, China. E-mail: [email protected].
Abstract: The BP neural network algorithm is used to construct a stable slope angle prediction model for open-pit mines, which can successfully predict the ultimate slope angle of the mine. At the same time, a multi-tool combination of Surpac, Madis, and Flac3D is used to create a numerical model for stable slope angle in mines. The model is used to test the final slope angle prediction structure for stable mines. Through a comprehensive analysis of the ore deposit model technology constructed by the series of realms, the economic parameters involved in the generation of realm boundaries are known, and specific primaries are pointed out with the error requirements of each parameter analyzed in the realm of series. A concrete solution is put forward to the issue of realm gap. From the point of view of the power and responsibility parameters, the series of realm production methods are analyzed, and the rapid generation methods of the realm of open-pit mine series are pointed out.
Keywords: BP neural network, open-pit mine, stable slope angle
