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Abstract In light of the complex and dynamic mechanical properties of evolving weak strata in open-pit mines, and the consequent difficulty of determining their mechanical parameters, this study uses the ultimate balance theory, along with the back analysis method combined with monitoring data on field displacement, to carry out parameter inversion using the FLAC3D numerical simulation software. The edge slope of a working pit of the Weijiamao open-pit mine was used as research object to this end. As the results obtained by the constitutive model were consistent with the field monitoring data, the evolving weak strata in the slope and the position of the landslide in the mine could be obtained. The landslide was directed northeast. The mechanism of the edge slope of the working pit was identified as unloading shear failure, and the feasibility of the method of parameter inversion was verified. The internal friction angle ϕ and cohesion C of evolving weak strata in the slope of the open-pit mine were also obtained, where this compensated for the deficiency of laboratory tests and enabled the transformation from qualitative to quantitative analysis. This can provide a reliable basis for the safe operation of open-pit mines.

The mining sequence affects the safe and efficient production of mines and the development and economic benefits of mining enterprises.In order to solve the problem of mining sequence during the fault-subsiding area of Heidaigou open-pit mine, three mining methods are proposed based on the coal and rock occurrence conditions, mine production status and equipment types.The evaluation indicators related to the program from the aspects of economy, technology and safety and used the three-dimensional modeling and simulated mining technology, qualitative and quantitative combination to determine the values of each parameter.Finally, The AHP-ideal point method was used to establish a comprehensive evaluation index system model to determine the optimal mining plan.

In order to solve the measurement problem of the production capacity of the dragline, a prediction method based on gray correlation combined with GA-BP neural network is proposed.The gray correlation analysis is carried out on the 12 influencing factors affecting the production capacity of the dragline, and the actual working hours, the out rate, the effective casting blast amount, and effective throw-out rate are selected.Four influencing factors greater than 0.7 were used as input variables and the monthly production capacity of the dragline was used as the output variable to establish GA-BP neural network and BP neural network prediction model.The results show that the maximum relative error of GA-BP neural network is 7.525%, the average relative error is 3.52%, the average error variance is 0.0156, and the number of iterations is 18 times.The performance is better than the conventional BP neural network.The GA-BP neural network model provides better and more accurate generalization performance for the production capacity of the dragline, and provides a more effective method for predicting the production capacity of the dragline.

In view of uncertainty of comprehensive evaluation index of security risks investigation and govern ability of coal mine, a set pair analysis and evaluation model was established. The model determines evaluation index system from two aspects of personnel factors and govern factors, taking positive and negative, similarity and dissimilarity connection degree into account to obtain a comprehensive connection degree, so as to realize quantitative evaluation of security risks investigation and govern ability of coal mine. The result of case analysis shows that the proposed model can reasonably evaluate security risks investigation and govern ability of coal mine, and the result is in line with the actual situation.