The prediction of seepage coefficient of coarse-grained soil by neurotic network

TANG Xiao-song; ZHENG Ying-ren; DONG Cheng

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The prediction of seepage coefficient of coarse-grained soil by neurotic network

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- The prediction of seepage coefficient of coarse-grained soil by neurotic network
- Vol. 28, Issue S1, (2007)
- 作者机构：
  
  后勤工程学院军事建筑工程系,重庆,40041
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU43
- Online First：28 March 2014，
  
  Published：2007
- 稿件说明：
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TANG Xiao-song, ZHENG Ying-ren, DONG Cheng. The prediction of seepage coefficient of coarse-grained soil by neurotic network[J]. 2007, 28(S1).
DOI：

TANG Xiao-song, ZHENG Ying-ren, DONG Cheng. The prediction of seepage coefficient of coarse-grained soil by neurotic network[J]. 2007, 28(S1). DOI：

摘要

粗颗粒土的渗透规律十分复杂，由于现有的一些定量公式考虑的影响因素过于简单，因此，无法准确确定其渗透系数的大小。以三峡库区现场取得的粗颗粒土为原料，通过渗透试验得到不同级配下土体的渗透系数，并利用神经网络较强的非线性动态处理能力对渗透系数进行预估，从而考虑了不同的颗粒级配对粗颗粒土渗透系数的影响。通过神经网络得到的预估值和渗透试验得到的试验值的对比分析可以看出，利用神经网络进行粗颗粒土渗透系数的预估是可行的，该方法能充分反映不同的颗粒级配的影响。

Abstract

The seepage rules of coarse-grained soil are very complicated. The present rational equations just consider some simple facts

therefore it is hard to identify accurate seepage factors. In this article

the coarse-grained soil obtained in Three Gorges Reservoir area is used to calculate the seepage factor of different graduation through the experiment

which is predicted through the powerful nonlinear and dynamic dealing capacity of the neurotic network. As a result

the influence of different graduation of the coarse-grained soil is taken into account. Through a comparison between the prediction from neurotic network and the experimental results

and the former can be used to predict the seepage factor of coarse-grained soil and this method can reflect the influence of different graduations.

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