Application of Support Vector Machine for Prediction of Slope Stability Coefficient Considering the Influence of Rainfall and Water Level

作者:Gui Lan, Tao; Zi Shun, Yao; Bin Zheng, Tan; Cong Cong, Gao; Yi Wen, Yao
来源:Applied Mechanics and Materials, 2016, 851: 840-845.
DOI:10.4028/www.scientific.net/amm.851.840

摘要

<jats:p>Slope stability estimation is a complex engineering problem involving many factors. A hybrid model based on the combination of finite element software GEO-STUDIO and support vector machine (SVM) is proposed to address the problem. The study took a high slope of Jingjiang reach of Yangtze River as the research object. Several important parameters, including values of geometric and geotechnical properties of slope as well as rainfall and water level data were used to establish the finite element model for the high slope. Besides, the validity of the model was estimate using the measured data of pore water pressure. The slope stability coefficients were calculated in GEO-STUDIO environment. And the data were used as the input samples to train and test SVM model. Results show that the agreement achieved in pore water pressure between measurement and analysis using the finite element model can be considered very reasonable. And the slope stability coefficient results by SVM coincided well with that of finite element analysis. It suggests that the proposed model has the potential to be a useful tool for the prediction of slope stability coefficient considering the influence of rainfall and water level.</jats:p>

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