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Intelligent Displacement Back Analysis for Excavation of An Underground Powerhouse in China

机译:中国地下厂房挖掘的智能位移回分析

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Back analysis is an effective method to obtain the rock mass mechanical parameters with measured displacements. But the traditional back analysis methods have some shortcomings, such as narrow scope of application and instability. The intelligent back analysis method which incorporates a neural network and a genetic algorithm can overcome the drawbacks mentioned above and give satisfactory results. In this paper, based on orthogonal design, neural network and genetic algorithms, the intelligent displacement back analysis was carried out for the excavation of an underground powerhouse of a pumped storage power station in China. First, a series of samples were selected to train the neural network so that the relations between displacement of rock mass and parameters were erected. Then the optimum values of parameters were gotten taking advantage of optimization of genetic algorithms. Substituting the obtained parameters into FDM software for forward computation, it was found that the calculated displacements agreed the measured data well. The intelligent back analysis method can be used as a powerful tool to find out the optimum mechanical parameters of rock mass.
机译:回分析是一种有效的方法,可以获得具有测量的位移的岩石质量机械参数。但传统的后分析方法具有一些缺点,如狭窄的应用范围和不稳定。包含神经网络和遗传算法的智能回分析方法可以克服上述缺点并提供令人满意的结果。本文基于正交设计,神经网络和遗传算法,对中国泵浦蓄能电站的地下电力公路进行了智能位移回分析。首先,选择一系列样品来训练神经网络,使岩石质量和参数位移之间的关系进行竖立。然后利用遗传算法优化参数的最佳值。将所获得的参数替换为FDM软件以进行前进计算,发现计算出的位移很好地同意了测量的数据。智能回分析方法可用作强大的工具,以找出岩体的最佳机械参数。

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