Assessment of highway slope failure using neural networks附视频

被引：0
|
作者：
Tsunglin LEE [1 ]
Hungming LIN [1 ]
Yuhpin LU [2 ]
机构：
[1] Department of Construction and Facility Management
[2] Department of Resource and Environment,Leader
来源：
Journal of Zhejiang University(Science A:An International Applied Physics & Engineering Journal) | 2009年 / 01期
关键词：
D O I：
暂无
中图分类号：
TU43 [土力学];
学科分类号：
0801 ; 080104 ; 0815 ;
摘要：
An artificial intelligence technique of back-propagation neural networks is used to assess the slope failure.On-site slope failure data from the South Cross-Island Highway in southern Taiwan are used to test the performance of the neural network model.The numerical results demonstrate the effectiveness of artificial neural networks in the evaluation of slope failure potential based on five major factors,such as the slope gradient angle,the slope height,the cumulative precipitation,daily rainfall and strength of materials.
引用
收藏
页码：101 / 108
页数：8
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