| 基于RBF神经网络的V撑施工过程风险分析 |
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| 引用本文： | 王立峰,肖子旺,王子强.基于RBF神经网络的V撑施工过程风险分析[J].武汉理工大学学报,2011(5):137-141. |
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| 作者姓名： | 王立峰 肖子旺 王子强 |
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| 作者单位： | 东北林业大学土木工程学院; |
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| 基金项目： | 国家自然科学基金(30700629) |
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| 摘 要： | 运用RBF神经网络(Radial Basis Function Neural Network)理论,分析了大夹角V撑施工期间最大风险因素可能发生的部位,并对V撑的结构失效风险性进行了定量分析。将有限元分析结果作为神经网络训练样本数据,利用径向基神经网络建立了基本变量和结构响应之间的隐性映射关系,根据蒙特卡洛原理进行模拟计算,最终得出V撑施工过程中各个危险截面出现结构失效的概率预估值。通过工程实例验证表明,基于径向基神经网络所建立的施工过程风险分析方法计算效率高,具有可行性和有效性,同时为V撑施工风险决策提供了理论依据。
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| 关 键 词： | RBF神经网络 蒙特卡罗 风险分析 V撑 |
Risk Analysis of V-shaped Pier in Construction Process by Means of RBF Artificial Neural Network |
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| WANG Li-feng,XIAO Zi-wang,WANG Zi-qiang.Risk Analysis of V-shaped Pier in Construction Process by Means of RBF Artificial Neural Network[J].Journal of Wuhan University of Technology,2011(5):137-141. |
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| Authors: | WANG Li-feng XIAO Zi-wang WANG Zi-qiang |
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| Affiliation: | WANG Li-feng,XIAO Zi-wang,WANG Zi-qiang(School of Civil Engineering,Northeast Forestry University,Harbin 150040,China) |
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| Abstract: | By taking finite element analysis results as sample data,an invisible mapping relationship between basic variables and structural response is established and a risk quantitative analysis method of high-risk location identification during V-shaped pier construction,by using RBF(Radial Basis Function) artificial neuron network is presented.Through a numerical simulation based on the principle of Monte Carlo,structural failure probability of each checking section of V-shaped pier during construction is calcula... |
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| Keywords: | radial basis function neural networks Monte Carlo risk analysis V-shaped pier |
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