Study On Intelligent Optimization Of Slope State Control Parameters Of High Slope In Mine With Gently Inclined Weak Interlayer

The slope control parameters mainly include step height h,step slope angleα,safety platform width l₁ and cleaning platform width l₂,which are the most direct foothold of the slope to take into account both safety production and economic benefits.A large number of gently inclined weak interlayers in mine slopes in southwest China have adverse effects on slope stability.Their special geological conditions make it difficult to balance safety and economy in slope design.In order to study the optimization method of slope state control parameters of this kind of mine,taking Huangshan limestone mine as the research object,the stability numerical calculation of 102 groups of slope state control parameter matrix is carried out.The sensitivity of slope stability coefficient and slope economic benefit to each slope state control parameter is analyzed respectively.The sensitivity index of compre-hensive benefit is established,and the optimization strategy of slope state control parameters is determined.The WOA-ELM algorithm is used to fit the calculation results of the stability coefficient,and an intelligent optimization method of slope control parameters considering economic benefits and slope stability is proposed.It has certain guiding significance for the engineering design of this kind of mine slope,and can provide a scientific method path for the safe production and rational utilization of resources of this kind of mine.The principal results are as follows:（1）According to the finite difference numerical calculation results of each scheme,it is determined that the weak interlayer is the key factor to control the slope stability.According to the safety regulations and numerical calculation results,the design safety factor Fs of the slope is determined.（2）Based on the correlation coefficient of slope control parameters and multiple regression standardized coefficient,the sensitivity of slope control parameters for slope stability is quantitatively analyzed,and the influence degree of each slope control parameter on the stability coefficient as h>α>l₂>l₁ is clarified.（3）Based on the geometric relationship between the residual ore amount and the slope control parameters,the slope control parameters.Based on the partial derivatives of the slope control parameters,the sensitivity of the slope control parameters to the economic benefit is quantitatively analyzed,and the influence degree of each slope control parameter on the stripping ore amount is determined asα>h>l₁>l₂.（4）A fitting model based on WOA-ELM algorithm is established to fit the mapping relationship between slope control parameters and stability coefficient,and the prediction of stability coefficient is realized.By applying the linear constraint that the stability coefficient is greater than the design safety factor to the prediction model,the stripping amount is set as the objective function to optimize the slope control parameters,and the intelligent optimization of slope control parameters based on WOA-ELM algorithm is realized.