卸荷条件下大理岩的BP神经网络模型
首发时间:2009-09-23
摘要:对锦屏二级水电站引水隧道的大理岩进行了保持轴向应变恒定的卸围压试验,得到大量试验数据。由于传统上Excel等对试验数据回归拟合的缺陷,所以在此讨论了基于MATLAB工具箱的BP神经网络在卸荷试验中的应用。根据实际情况,设置适当的BP神经网络参数,,对卸围压条件下的峰前和峰后试验数据进行训练和仿真,并建立了卸围压条件下的BP神经网络模型。结果表明,BP神经网络模型的预测值和试验值相当吻合,模拟效果比较理想。
关键词: 卸围压 峰前、峰后应力-应变关系 BP神经网络模型
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Unloading Marble Umder The Conditions of The BP Neural Network Model
Abstract:Jinping Hydropower Station on the marble tunnel had to maintain a constant axial strain of unloading confining pressure test, to be a large number of experimental data. Because traditionally, such as the use of EXCEL regression fitting of test data deficiencies discussed in this toolbox of MATLAB-based BP neural network in unloading test. According to the actual situation, set the appropriate parameters of BP neural network, unloading confining pressure of the peak under the conditions of pre-and post-peak test data for training and simulation, and the establishment of dumping under the conditions of confining pressure of the BP neural network model. The results show that, BP neural network model predicted and experimental values coincide with ideal simulation results.
Keywords: unloading confining pressure stress-strain relationship at pre-peak and post-peak BP neural network model
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