铁道科学与工程学报Issue(3)：107-110,4.
客运专线铁路路基粗粒土填料最大干密度的BP神经网络预测
Prediction model of maxi mu m dry density of coarse grained soil using BP neural networks
摘要
Abstract
Taking the fillers of the coarse-grained soil in Zhijiang north station of Shanghai-Kunming passen-ger dedicated line as the research object,the vibration compaction test was conducted to study maximum dry den-sities 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 gran-ular compositions,grading index and fractal index was established.Based on the backwards error propagation al-gorithm and the result of the maximum dry density test,the model established in this paper performs well in pre-dicting the maximum dry density of the coarse-grained soil of various granular compositions.关键词
粗粒土/最大干密度/神经网络/预测Key words
coarse-grained soil/maximum dry density/neural network/prediction分类
交通工程引用本文复制引用
刘源,宋晓东,聂志红,王翔..客运专线铁路路基粗粒土填料最大干密度的BP神经网络预测[J].铁道科学与工程学报,2014,(3):107-110,4.基金项目
铁道部科技研究开发计划资助项目 （）
