Application of SSA-MLP model to stability prediction of rock slope
In this paper,a new method of rock slope stability prediction and parameter inversion is proposed by combining the rock strength criterion,swarm intelligence algorithm,and artificial neural network theory.Hoek-Brown(H-B)strength criterion is a classical method used to determine the mechanical parameters of rock mass,which can reflect the nonlinear failure characteristics of rock mass deformation and displacement,and has good applicability in the stability analysis of rock slopes.Therefore,based on the parameters of the H-B criterion,the index system of rock slope stability prediction is constructed.Then,according to the complex nonlinear characteristics of slope engineering stability problem,a prediction model of Multi-Layer Perceptron(MLP)neural network improved by Sparrow Search Algorithm(SSA)is proposed for the prediction of safety factor and parameter inversion of rock slope.The parameter optimization function of the sparrow search algorithm is used to optimize the connection weights and thresholds of the multi-layer perceptron neural network,and the SSA-MLP neural network model with higher prediction accuracy is obtained.Besides,according to the geometric parameters and H-B criterion parameters of 1 085 sets of rock slopes collected as input variables,and the slope safety factor solved by the Bishop method based on the limit equilibrium theory as output variables,the training learning and performance evaluation of the SSA-MLP model are carried out,and compared with other network models.It is analyzed that the model had high feasibility.In addition,the sensitivity analysis between the safety factor and the characteristic index is carried out by using the SSA-MLP model and the Kendall correlation coefficient.Finally,the model is applied to 25 slope cases,and the parameter inversion of the disturbance coefficient(D)and the geological strength index(GSI)in engineering cases is carried out to further verify the effectiveness of the model The results show that the model has fast convergence speed and high precision,which provides a new idea for slope stability analysis and parameter quantification.
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维普
