The Application of BP Neural Network in the Research of the Landslide Stability

Abstract:

According to the basis of analysis of stability evaluation and prediction of landslide research status, discusses the factors influencing the stability of landslide and slope stability analysis methods; analyzing advantages and disadvantages of neural network research method, operability of evaluation of landslide stability analysis, select average slope, slope of the invading front, sliding surface slope, the maximum annual average rainfall, the recent slide situation, human engineering activities as indicators of slope stability evaluation， has established based on BP neural network landslide stability analyses and applying Matlab toolbox to train network. The error analysis result indicate the sample training result and the actual situation tally basically, prove this model can tally with the project reality.

• Periodical: Advanced Materials Research (Volumes 594-597)
• Pages: 2290-2295
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.594-597.2290
• Online since: November 2012
• Authors: Peng Li Li, Wei Ping Tian, Jia Chun Li
• Keywords: BP Neural Network (BPNN), Landslide, Nonlinear, Stability Analysis

References

[1] Hung-Ming Lin, Shun-Kung Chang, Jian-Hong Wu,2009.Neural network-based model for assessing failure potential of highway slopes in theAlishan, Taiwan Area: Pre- and post-earthquake investigation. Engineering Geology 104 , 280–289.

DOI: 10.1016/j.enggeo.2008.11.007

[2] Ni, S.H., Lu, P.C., Juang, C.H., 1995. A fuzzy neural network approach to evaluation of slope failure potential. Journal of Microcomputers in Civil Engineering 11, 59–66.

DOI: 10.1111/j.1467-8667.1996.tb00309.x

[3] Lee, S., Ryu, J.H. Won, J.S., Prak, H.J., 2004. Determination and application of the weights for landslide susceptibility mapping using an artificial neural network. Engineering Geology 71, 289–302.

DOI: 10.1016/s0013-7952(03)00142-x

[4] Nefeslioglu, H.A., Gokceoglu, C., Sonmez, H., 2008. An assessment on the use of logistic regression and artificial neural networks with different sampling strategies for the preparation of landslide susceptibility maps. Engineering Geology 97 (3–4), 171–191.

DOI: 10.1016/j.enggeo.2008.01.004

[5] Wang, H.B., Xu, W.Y., Xu, R.C., 2005. Slope stability evaluation using Back Propagation Neural Networks. Engineering Geology 80, 302–315.

DOI: 10.1016/j.enggeo.2005.06.005

[6] Sun Branch. Rock slope stability analysis [M]. Beijing: Science Press, 1998.

[7] Cheng Xiangjun, Neural Network and Its Application [M]. Beijing: National Defence Industry Press,1995,51-62.

[8] Li Pengli. Analysis of Landslide Stability and Landslide Prediction Based on Neural Network[D]. Chang'an University,2011.7