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黄土场地大型浸水试验湿陷沉降预测的Elman方法
引用本文:韩晓萌,王家鼎,谷天峰,薛建功.黄土场地大型浸水试验湿陷沉降预测的Elman方法[J].地下水,2008,30(6):111-113.
作者姓名:韩晓萌  王家鼎  谷天峰  薛建功
作者单位:1. 西北大学地质学系大陆动力学国家重点实验室,陕西,西安,710069
2. 陕西省公路局,陕西,西安,710068
基金项目:国家自然科学基金 , 教育部高等学校博士学科点专项科研基金  
摘    要:收集郑西高速铁路湿陷性黄土场地现场大型浸水试验资料,运用MATLAB建立了黄土场地湿陷沉降的Elman神经网络预测模型。通过对样本的训练和预测,表明该模型预测的结果与实际湿陷沉降比较接近,是一种比较理想的预测方法。

关 键 词:Elman神经网络  黄土湿陷  沉降  高速铁路地基  浸水试验

The Elman Method for Forecasting the Large Water Immersion Collapsibility Test in the Loess Field
HAN Xiao-meng,WANG Jia-ding,GU Tian-feng,XUE Jian-gong.The Elman Method for Forecasting the Large Water Immersion Collapsibility Test in the Loess Field[J].Groundwater,2008,30(6):111-113.
Authors:HAN Xiao-meng  WANG Jia-ding  GU Tian-feng  XUE Jian-gong
Institution:HAN Xiao-meng1,WANG Jia-ding1,GU Tian-feng1,XUE Jian-gong (1 Department of Geology,Northwest University /The Key Laboratory of Continental Dynamics in China,Xi\'an,Shaan\'xi,710069,Highway bureau of Shaanxi province Xi\'an 710068,Shaanxi)
Abstract:The paper collects data about the field large water immersion test in the wet sedimentation loess of ZhengXi High-Speed Railway,making of the MATLAB to establish a model of Elman neural network to forecast loess field collapsibility settlement.Through to training and forecasting the samples,compared with the forecasted result,it is shown that the forecasted results are approach,so it's one perfect method.
Keywords:Elman neural network  loess collapsibility  Settlement  High-Speed Railway foundation and water immersion test  
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