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- W2377189792 abstract "The characteristics of the inlet of flood discharging tunnel of Jinchuan Hydraulic Power Plant are natural high and steep slope,obvious inclined deformation of rock stratum and poor quality of rock mass,which is adverse to the stability of the slope. It chose BP neural network method to inverse analysis of the intensity parameter. Determining the minimum safety factor of slope according to the importance of the slope and norms,and deciding the inversion conditions and slip zone on the base of slope deformation. Neural network training samples were organized by limit equilibrium,the safety factor as the network input,C and φ as the output,and taking them as the limit equilibrium and finite element strength reduction calculation parameters to test. The results show that the error of BP neural network and limit equilibrium methods is within 1%,and finite element strength reduction calculating the average shear strength parameters and safety factor of shallow deformation are also consistent with BP neural network calculation results,which indicates that the BP neural network to parameter inverse analysis is reliable." @default.
- W2377189792 created "2016-06-24" @default.
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- W2377189792 date "2014-01-01" @default.
- W2377189792 modified "2023-09-26" @default.
- W2377189792 title "BP Neural Network Applied to Strength Parameters Inverse Analysis in Unloading Rock Mass" @default.
- W2377189792 hasPublicationYear "2014" @default.
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