路基工程Issue(3)：54-57,4.
基于BP神经网络冻土强度预测模型研究
Study on Prediction Model of Frozen Soil Strength Based on Back-propagation Neural Network
摘要
Abstract
Artificial freezing method has been used in Suzhou subway interconnecting channel construction as an auxiliary technique. However, there is no normalized parameter about frozen soil strength in Suzhou area for design at present. Therefore, a prediction model is established in this paper considering the influence of temperature, water content and dry density on typical frozen soil strength in Suzhou subway using artificial neural network to map the non-linearity among these influencing factors. The result shows that BP network has higher solving capability and is more accurate than other linear regression methods, from which the predicted value is closer to measured value. In addition, it is simple and practical. It would provide a new way to obtain the parameter which cannot be achieved in test.关键词
BP神经网络/抗压强度/温度/含水率/干密度Key words
back-propagation neural network/ compressive strength/ temperature/ water content/ dry density分类
建筑与水利引用本文复制引用
贺俊,杨平,董朝文..基于BP神经网络冻土强度预测模型研究[J].路基工程,2011,(3):54-57,4.基金项目
江苏省"六大人才高峰"资助项目 （）
苏州市科技局专项课题(ZXJ0802) （ZXJ0802）
