Slope Reliability Analysis Based on BP Neural Network
A slope reliability calculation method based on BP neural network response surface is proposed to efficiently and accurately calculate the reliability index of slope stability.A functional function of slope structural reliability was established based on the finite element strength reduction method and structural reliability theory.The response characteristics of the slope structure were learned and fitted using a BP neural network.The Monte Carlo simulation method was used to conduct important sampling at the critical state of the slope,and the stability reliability index of the slope was calculated.The feasibility of this method was verified using the Hongchen slope project as an example.The results indicate that the BP neural network can accurately fit the response characteristics of slope struc-tures;The slope reliability index obtained based on BP neural network is1.255,with a relative error of only-0.51%compared to the finite element calculation;The reliability index calculated by the proposed method has high accuracy,and the results are slightly con-servative.The overall slope structure is in a stable state.
slope engineeringreliabilitystability coefficientBP neural networkMonte Carlo method
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