Prediction of Slope Stability Based on GA-BP Hybrid Algorithm

Xinhua Xue, Yangpeng Li, Xingguo Yang, Xin Chen, Jian Xiang


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.


GA-BP hybrid algorithm; Jinping I hydropower station; left abutment slope; stability

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