Slope stability forecasting method based on Grey and BP Neutral Network combined model
Xiong Mianguo · Nonferrous Metals · 2012
Based on the studies before,BP(Back Propagation) Neural Network and Grey Theory are studied in this paper.With the using conditions,as well as the advantages and disadvantages,GM(1,1) model is established under different sample intervals of the same known slope,and different forecasting results are obtained.Using several Grey results as input data,to combine them with BP Neural Network,and then the combination results are obtained.The evaluation of slope stability forecasting is proposed based on example-inference of Grey Neural Network.According to the complicated flexible influences and strong uncertainty of slope stability,the slope example index model is set up.Finally,the current slope stability evaluation can be realized through Grey model preprocessing of the slope stability factors and Neural Network study of slope examples.