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In order to forecast the security risk of cement-soil gravity wall, an index system whose function is to forecast the security of cement-soil gravity wall is established from four aspects of soil properties, mechanical properties of mixer, materials, error of a pile position and verticality deviation. We introduce BP neural network to the training of sample data, then BP neural network model is established to predict the security risk of cement-soil gravity retaining wall. Combined with a base engineering project, the validity and practicability of this forecast is testified. Keywords-cement-soil gravity retaining wall; safety forecast ;BP neural network

Study on prediction of cement-soil gravity retaining wall security risk based on BP