Abstract：Using an inversion analysis to determine the mechanical parameters of a dam and its foundation from monitoring data is of great significance to safety evaluation. An inversion analysis method was developed based on an adaptive genetic algorithm and a BP neural network. The analysis used the weighted absolute percentage error as the objective function to determine the mechanical parameters from multi-point monitoring data and nonlinear numerical simulations. Deformation data from 25 measurement points was used to determine 11 key mechanical parameters for the dam concrete, foundation rock mass and structural plane. The results show that the inversion values are in good agreement with measured data. The inversion accuracy is improved by using the material parameters as the input layer and the deformation as the output layer. The effects of the neural network topology, objective function and the number of training samples on the inversion results was analyzed.
庄文宇, 张如九, 徐建军, 殷亮, 魏海宁, 刘耀儒. 基于IAGA-BP算法的高拱坝-坝基力学参数反演分析[J]. 清华大学学报（自然科学版）, 2022, 62(8): 1302-1313.
ZHUANG Wenyu, ZHANG Rujiu, XU Jianjun, YIN Liang, WEI Haining, LIU Yaoru. Inversion analysis to determine the mechanical parameters of a high arch dam and its foundation based on an IAGA-BP algorithm. Journal of Tsinghua University(Science and Technology), 2022, 62(8): 1302-1313.
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2022, Vol. 62 
