The application of artificial neural network in complicated rockmass quality classification of a hydraulic power station on the right bank of Lancang River

The paper applies the method of the back propagation artificial neural network on a hydraulic power station on the Lancang River, Yunnan Province,choosing six influential factors on the rock mass quality as the input variables,such as one axis compressive strength of rock, sound degree coefficient of rock mass, rock quality designation, roughness degree coefficient of joint surface, alteration coefficient of joint surface, permeability coefficient,and classifies the complicated rock mass on the right bank of the dam foundation. Through comparison analysis, the result of predicting the rock mass is exact and credible after the model of the back propagation artificial neural network learning enough times.The application has gained a good effect.