摘要
建立了人工神经网络的边坡稳定预测模型,收集了较多的样本进行网络训练,结果表明,所建立的模型预测精度较高,简便易行,具有工程应用价值。通过人工神经网络的训练发现,边坡的坡度、内摩擦角、凝聚力对边坡的安全系数影响较大。对于水库边坡来说,水的渗流、水压力和坝高均对边坡的稳定性有较大的影响。
The prediction of the slope stability is presented on the artificial neural network,and then many a sample are collected to carry on the network training. The results show that the predictive models are accurate and easy to operate, thus the method is profitable in engineering. The consequences after the artificial neural network training illustrate that the safety factor are ＂affected largely by the parameters of the slope stability-the slope, rubbing angle inside and coagulate force. To slope of reservoir, the safety factor is affected by seepage, the pressure of water and height of dam.
出处
《苏州科技学院学报（工程技术版）》
CAS
2006年第2期21-25,共5页
Journal of Suzhou University of Science and Technology （Engineering and Technology）
关键词
预测
边坡稳定
人工神经网络
渗流
prediction
slope stability
artificial neural network
seepage
