PREDICTION OF SLOPE STABILITY BASED ON GA-BP HYBRID ALGORITHM

被引：17
|
作者：
Xue, Xinhua [1 ]
Li, Yangpeng [1 ]
Yang, Xingguo [1 ]
Chen, Xin [1 ]
Xiang, Jian [2 ]
机构：
[1] Sichuan Univ, Coll Water Resource & Hydropower, State Key Lab Hydraul & Mt River Engn, Chengdu 610065, Sichuan, Peoples R China
[2] Sinohydro Bur 7 Co Ltd, Chengdu 610081, Sichuan, Peoples R China
来源：
NEURAL NETWORK WORLD | 2015年 / 25卷 / 02期
关键词：
GA-BP hybrid algorithm; Jinping I hydropower station; left abutment slope; stability;
D O I：
10.14311/NNW.2015.25.010
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Safety monitoring and stability analysis of high slopes are important for high dam construction in mountainous regions or precipitous gorges. Slope stability estimation is an engineering problem that involves several parameters. To address these problems, a hybrid model based on the combination of Genetic algorithm (GA) and Back-propagation Artificial Neural Network (BP-ANN) is proposed in this study to improve the forecasting performance. GA was employed in selecting the best BP-ANN parameters to enhance the forecasting accuracy. Several important parameters, including the slope geological conditions, location of instruments, space and time conditions before and after measuring, were used as the input parameters, while the slope displacement was the output parameter. The results shown that the GA-BP model is a powerful computational tool that can be used to predict the slope stability.
引用
收藏
页码：189 / 202
页数：14
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