Prediction model of maximum dry density of coarse grained soil using BP neural networks
Yuan Liu · Journal of Railway Science and Engineering · 2014
Taking the fillers of the coarse-grained soil in Zhijiang north station of Shanghai-Kunming passenger dedicated line as the research object,the vibration compaction test was conducted to study maximum dry densities under different granular compositions. Considering the non-linear relations between granular compositions and maximum dry densities,a BP neural network prediction model of which the input layer was consisted of granular compositions,grading index and fractal index was established. Based on the backwards error propagation algorithm and the result of the maximum dry density test,the model established in this paper performs well in predicting the maximum dry density of the coarse-grained soil of various granular compositions.