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BP神经网络在灰坝动力计算中的应用
引用本文:陈建斌,何刚雁,范伟.BP神经网络在灰坝动力计算中的应用[J].土工基础,2012,26(4):85-87,105.
作者姓名:陈建斌  何刚雁  范伟
作者单位:1. 武汉市政工程设计研究院有限责任公司,武汉,430023
2. 武汉市城建基金办污水全收集全处理项目建设管理办公室委员会,武汉,430050
摘    要:针对灰坝动力计算模型参数的不确定性和复杂性,以大量室内动力试验所得参数为预测样本,以粉煤灰的基本物理特性参数作为输入值,利用BP神经网络强大的非线性映射能力,建立了灰坝动力本构方程参数的预测模型。将其应用于某电厂灰坝的动力有限元计算中,计算所得灰坝的模态参数、动力响应和破坏性态与模型试验结果进行分析比较,取得了比较一致的结论。最后提出了一些对灰坝抗震有价值的建议。

关 键 词:灰坝  BP神经网络  预测模型  动力有限元

Application of BP Neural Network in the Dynamic Calculation of Fly-ash Dam
CHEN Jianbin , HE Gangyan , FAN Wei.Application of BP Neural Network in the Dynamic Calculation of Fly-ash Dam[J].Soie Engineering and Foundation,2012,26(4):85-87,105.
Authors:CHEN Jianbin  HE Gangyan  FAN Wei
Affiliation:1 (1.Wuhan Municipal Engineering Design and Research Institute Co.Ltd,Wuhan 430023; 2.Office of Waste Water Collection and Treatment Project,Wuhan Municipal Construction Foundation,Wuhan 430050)
Abstract:Considering the uncertainty and complexity of dynamic parameters of a computational model used in the fly-ash dam simulation,a predictive model of the dynamic parameters of ash dam simulation is established.The sampling pool used in the predictive model is obtained from laboratory tested soil parameters.The model also adopts the predictability of the Back Propagation(BP) neural network.The dynamic response of a fly-ash dam of a power plant was analyzed and the numerical results were compared with the measured results.This analytical approach provides useful recommendations for the response of a fly-ash dam under a seismic condition.
Keywords:Fly-ash Dam  Back Propagation(BP) Neural Network  Predictive Model  dynamic FEM
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