| 径向基函数神经网络在大坝安全监测数据处理中的应用 |
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| 引用本文： | 张晓春,徐晖,邓念武,陈仁喜.径向基函数神经网络在大坝安全监测数据处理中的应用[J].武汉大学学报(工学版),2003,36(2):33-36. |
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| 作者姓名： | 张晓春 徐晖 邓念武 陈仁喜 |
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| 作者单位： | 1. 武汉大学水利水电学院,湖北,武汉,430072
2. 武汉大学资源与环境科学学院,湖北,武汉,430072 |
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| 摘 要： | 建立了大坝安全监测数据处理坝段挠度预测的径向基神经网络模型 ,与通常的BP神经网络模型进行对比 ,并与实测结果进行校核 .结果表明 ,对于所研究的问题 ,径向基函数网络避免了BP网络的局部极小及收敛速度慢等缺点 ,在精度、训练速度等方面优于BP网络
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| 关 键 词： | 径向基 人工神经网络 大坝安全监测 |
| 文章编号： | 1671-8844(2003)02-033-04 |
| 修稿时间： | 2002年7月16日 |
Application of a radial basis function neural network model to data processing technique of dam safety monitoring |
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| ZHANG Xiao_chun\,XU Hui\,DENG Nian_wu\,CHEN Ren_xi\.Application of a radial basis function neural network model to data processing technique of dam safety monitoring[J].Engineering Journal of Wuhan University,2003,36(2):33-36. |
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| Authors: | ZHANG Xiao_chun\ XU Hui\ DENG Nian_wu\ CHEN Ren_xi\ |
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| Affiliation: | ZHANG Xiao_chun\+1,XU Hui\+1,DENG Nian_wu\+1,CHEN Ren_xi\+2 |
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| Abstract: | A radial basis function neural network model to data processing technique of dam safety monitoring is established. The prediction model based on radial basis function network is studied through experimental data and verified by additional data successfully. Another network model based on back propagation network is also trained for comparision . The results show that the radial basis function network is much better than back propagation network in accuracy and speed of training for the problem studied. |
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| Keywords: | radial basis function artificial neural network dam safety monitoring |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ |
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