| 基于主成分分析与BP神经网络模型的大坝渗流监测资料分析 |
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| 引用本文： | 田伟,魏光辉,高强. 基于主成分分析与BP神经网络模型的大坝渗流监测资料分析[J]. 大坝与安全, 2009, 0(5): 29-31,35 |
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| 作者姓名： | 田伟 魏光辉 高强 |
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| 作者单位： | 1. 新疆水利水电科学研究院,新疆,乌鲁木齐,830049
2. 新疆农业大学水利与土木工程学院,新疆,乌鲁木齐,830052 |
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| 摘 要： | 大坝渗流观测资料分析中,各因子间常存在不同程度的相关性,这种相关性有时会对分析效果产生较大的影响,另外,通常的回归模型为线性模型,难以精确反映一般为非线性函数的因变量的变化规律。针对上述问题,本文将主成分分析和神经网络相结合,建立大坝渗流观测数据的主成分神经网络模型,经实例计算,该模型的预报精度较高。
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| 关 键 词： | 大坝渗流 主成分分析 BP神经网络 预报 |
Seepage data analysis based on principal component analysis and BP neural network |
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| TIAN Wei,WEI Guang-hui , GAO Qiang // Xinjiang Institute of Hydraulic , Hydropower Research. Seepage data analysis based on principal component analysis and BP neural network[J]. Large Dam & Safety, 2009, 0(5): 29-31,35 |
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| Authors: | TIAN Wei WEI Guang-hui GAO Qiang // Xinjiang Institute of Hydraulic & Hydropower Research |
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| Abstract: | Correlation between factors has an effect on the analysis of dam seepage observation data.Besides,the regression model is usually linear and it can hardly reflect the change of a dependent variable which is nonlinear function.In consideration of the above problems,and in combination with principal component analysis and BP neural network.A principal component analysis and BP neural network model is set up for analysis of dam seepage observation data in this paper.The result of an example shows that the pred... |
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| Keywords: | dam seepage principal component analysis BP neural network prediction |
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