A Neural Network Method for Analyzing Compass Slope Stability of the Highway
WU Shuren · 2004
Slope stability generally depends on some elusive and nonlinear factors. The artificial neural network is characterized by parallel processing of data and information, high fault tolerance and antinoise capacities. It can self-adaptively derive complicated nonlinear relations from sample examples and simulate human brain activities and is therefore suited for evaluating the stability of the nondeterministic slope. The authors have created a neural network BP model for slope stability analysis. On the basis of collected slope analyzing examples,the BP model was used to examine slope stability along Section K250 arterial highway between Guilin and Liu zhou. The result shows that the neural network method is very effective in analyzing slope stability.