摘要
针对吹填土路基处理技术决策中是否需要进行处理,是深层处理还是浅层处理的问题,基于BP神经网络构造了软土厚度、软土压缩模量、地表硬壳层厚度和吹填土路堤高4个参数的吹填土路基处理方式决策模型。通过BP神经网络模型进行学习、训练以及回判和预测,实现预测结果和实际处理结果基本一致。
Against the technical decision of treatment, deep treatment or shallow treatment for dredger fill subgrade, the decision model thereof is established on the basis of BP neural network, which is related to 4 parameters, including thickness and compression modulus of soft soil, thickness of hard crust layer of earth＇ s surface and height of dredger fill embankment. The study, training, back-judge and pre-judge are carried out through BP neural network model and the consistency between predicted and the actual results are realized substantially.
出处
《路基工程》
2012年第2期151-154,共4页
Subgrade Engineering
关键词
吹填土
路基
BP人工神经网络
dredger fill
subgrade
BP artificial neural network
