[1]赵林,王丽..基于BP神经网络的结构系统跟踪辨识方法[J].郑州大学学报(工学版),2005,26(01):50-53.[doi:10.3969/j.issn.1671-6833.2005.01.013]
ZHAO Lin,Wang Li.Structural system tracking identification method based on BP neural network[J].Journal of Zhengzhou University (Engineering Science),2005,26(01):50-53.[doi:10.3969/j.issn.1671-6833.2005.01.013]
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基于BP神经网络的结构系统跟踪辨识方法(
)
《郑州大学学报(工学版)》[ISSN:1671-6833/CN:41-1339/T]
- 卷:
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26卷
- 期数:
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2005年01期
- 页码:
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50-53
- 栏目:
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- 出版日期:
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1900-01-01
文章信息/Info
- Title:
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Structural system tracking identification method based on BP neural network
- 作者:
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赵林; 王丽.
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同济大学建筑工程系,上海,200092, 黄河水利职业技术学院土木工程系,河南,开封,475001
- Author(s):
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ZHAO Lin; Wang Li
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- 关键词:
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跟踪识别; 结构系统辨识; BP神经网络; 地震荷载
- Keywords:
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- DOI:
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10.3969/j.issn.1671-6833.2005.01.013
- 文献标志码:
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A
- 摘要:
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针对人工神经网络在结构系统辨识中存在的问题,提出一种基于BP神经网络的跟踪辨识方法.通过将实际结构模型分为一个机理模型和一个实时误差模型,前者基于常规的BP神经网路通过离线训练而成,而后者通过小型的BP神经网络实时辨识系统误差,进而使这种经过改进的系统识别网络能够具有动态递阶识别系统的能力.计算机仿真分析表明,这种方法可有效地减小由于不同外荷载作用引起的结构系统辨识误差,提高人工神经网络在系统辨识中的精度和可靠度.
- Abstract:
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Aiming at the problems of artificial neural networks in the identification of structural systems, a tracking recognition method based on BP neural networks is proposed. By dividing the actual structural model into a mechanism model and a real-time error model, the former is trained offline based on the conventional BP neural network, while the latter identifies the systematic error in real time through a small BP neural network, so that the improved system recognition network can have the ability of dynamic hierarchical recognition system. Computer simulation analysis shows that this method can effectively reduce the identification error of structural system caused by different external loads, and improve the accuracy and reliability of artificial neural network in system identification.
更新日期/Last Update:
1900-01-01