| 改进的遗传神经网络模型及其在变形监控中的应用 |
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| 引用本文： | 李珂,岳建平,马保卫,秦茂芬.改进的遗传神经网络模型及其在变形监控中的应用[J].大坝与安全,2007(5):65-68. |
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| 作者姓名： | 李珂 岳建平 马保卫 秦茂芬 |
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| 作者单位： | 河海大学土木工程学院,江苏,南京,210098 |
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| 摘 要： | 针对基本遗传算法(SGA)收敛速度慢、局部寻优能力差等缺陷,采用十进制编码,引入改进的算术交叉、非均匀变异操作等算法,分析和建立了改进的遗传神经网络(IGA-BP)模型,并将该模型应用于大坝水平位移的预测.结果表明,该模型在收敛速度、预报精度等方面比传统模型有较大的改善.
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| 关 键 词： | 遗传算法 IGA-BP 变异算子 数学模型 |
| 文章编号： | 1671-1092（2007）05-0065-04 |
| 修稿时间： | 2007-06-25 |
Improved genetic neural network model and its application to deformation monitoring |
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| LI Ke, YUE Jian-ping, MA Bao- wei and et al..Improved genetic neural network model and its application to deformation monitoring[J].Large Dam & Safety,2007(5):65-68. |
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| Authors: | LI Ke YUE Jian-ping MA Bao- wei and |
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| Affiliation: | Hohai University |
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| Abstract: | In view of the disadvantages of simple genetic algorithm: low convergence rates,inferior ability in local optimization and so on,a decimal encoding scheme,improved arithmetic crossover and non-uniform mutation operation were adopted to improve IGA,then an IGA-BP model was analyzed and built.The experiment in which the IGA-BP model was applied to forecast dam horizontal displacement indicated the IGA-BP model was much better than traditional models in convergence speed and prediction precision. |
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| Keywords: | Genetic Algorithm IGA-BP mutation operator mathematical model |
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