Application of neural network methods based on gray theory the flood proving slope stability Analysis

LIN Yu-liang; LU Dan-mei; YANG Er-jing

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Application of neural network methods based on gray theory the flood proving slope stability Analysis

更新时间：2026-06-25

- Application of neural network methods based on gray theory the flood proving slope stability Analysis
- Vol. 27, Issue S2, (2006)
- 作者机构：
  
  1. 广西大学土木建筑工程学院,南宁,530004
  2. 广西水电工程设计院,南宁,530022
- 作者简介：
- 基金信息：
- DOI：
  CLC： TU443
- Online First：16 December 2006，
  
  Published：2006
- 稿件说明：
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LIN Yu-liang, LU Dan-mei, YANG Er-jing. Application of neural network methods based on gray theory the flood proving slope stability Analysis[J]. 2006, 27(S2).
DOI：

LIN Yu-liang, LU Dan-mei, YANG Er-jing. Application of neural network methods based on gray theory the flood proving slope stability Analysis[J]. 2006, 27(S2). DOI：

摘要

灰关联分析神经网络方法首先是对防洪堤边坡稳定性影响因素进行灰关联分析，得出各因素影响程度的大小排序，然后建立该工程的神经网络模型，选择灰关联分析得到的优势因子作为样本输入以及关联度作为网络权值确定的一个因素，利用大量南宁市防洪堤边坡工程实例对网络进行训练学习，最后用训练成功的网络对工程进行预测。预测的结果与实际情况进行对比表明，这个方法能够满足南宁市防洪堤边坡稳定性预测的要求。

Abstract

A neural network method based on gray theory is presented

in this method

the influential influence factors on slope stability of flood embankment are analyzed by gray correlation to get the order of each influential factor; then the advantage factors of gray correlation analysis are chosen to train the neural network; and the correlation degrees are taken as a factor to decide the weighted coefficients; finally the trained neural network is used to predict the engineering. This method has been applied to the slope stability analysis of Nanning flood proving slopes. Compared with the actual situation

this method can satisfy the requirements for slope stability forecast of Nanning flood embankments.

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