| 改进模糊神经网络模型及其在大坝监测中的应用 |
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| 引用本文： | 黎昵,岳建平,段鹏. 改进模糊神经网络模型及其在大坝监测中的应用[J]. 水电自动化与大坝监测, 2007, 31(1): 74-76 |
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| 作者姓名： | 黎昵 岳建平 段鹏 |
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| 作者单位： | 河海大学土木工程学院,江苏省南京市,210098 |
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| 摘 要： | 鉴于传统模糊神经网络计算繁琐、模型精度较低、难以收敛等问题,在大坝位移的监测数据分析中应用改进的模糊神经网络及改进的反向传播(BP)网络算法,并建立了相应的网络模型.大量的数据分析计算表明,该模型收敛快,且精度优于常规的模糊神经网络和传统的统计模型.
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| 关 键 词： | 模糊神经网络 BP算法 动量因子 监控模型 |
| 收稿时间： | 2006-10-10 |
| 修稿时间： | 2006-11-29 |
Improved Fuzzy Neural Network Model and Its Application to Dam Monitoring |
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| LI Ni,YUE Jianping,DUAN Peng. Improved Fuzzy Neural Network Model and Its Application to Dam Monitoring[J]. HYDROPOWER AUTOMATION AND DAM MONITORING, 2007, 31(1): 74-76 |
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| Authors: | LI Ni YUE Jianping DUAN Peng |
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| Abstract: | Considering complicated computation, low model precision and convergence problem of the traditional fuzzy neural network, an improved fuzzy neural network and its BP algorithm are used to analyze the data of dam displacement monitoring, and a network model is established. Large numbers of data analysis show that the improved network model converges rapidly and has a higher precision than the traditional fuzzy neural network and statistical model. |
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| Keywords: | fuzzy neural network BP algorithm momentum efficient monitoring model |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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