摘要
砂土地震液化问题是岩土地震工程学的重要研究课题之一。在分析模糊神经网络原理的基础上,利用减法聚类算法对自适应模糊推理系统进行优化,并建立了砂土地震液化的模糊神经网络模型。然后,将该模型用于实际工程的砂土液化判别中,并与传统砂土液化判别方法结果进行对比。判别结果表明:文中建立的模糊神经网络模型具有较强的学习功能,用于砂土地震液化判别中是可行的和有效的。
Sand liquefaction is one of important issues in the research field of geotechnical earthquake engineering.The adapted fuzzy reasoning system is optimized by adopting the algorithm of subtraction clustering based on the analysis of fuzzy neural network,and an adaptive fuzzy neural network model of sand liquefaction is proposed and applied to an actual engineering.The forecasted results show that the proposed model in this article is feasible and effective.
出处
《地震工程与工程振动》
CSCD
北大核心
2012年第2期172-177,共6页
Earthquake Engineering and Engineering Dynamics
基金
国家自然科学基金项目(50909068)
关键词
减法聚类
自适应模糊神经网络
液化
判别
subtraction clustering
adaptive fuzzy neural network
liquefaction
prediction
