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| 基于遗传单纯形神经网络的大坝变形监控模型 | |
| 引用本文： | 闫滨,周晶,高真伟.基于遗传单纯形神经网络的大坝变形监控模型[J].水力发电学报,2007,26(4):110-114. |
| 作者姓名： | 闫滨 周晶 高真伟 |
| 作者单位： | 1. 大连理工大学,土木水利学院,辽宁,大连,116024;沈阳农业大学,水利学院,沈阳,110161 2. 大连理工大学,土木水利学院,辽宁,大连,116024 3. 辽宁省水利厅,沈阳,110003 |
| 摘 要： | 本文针对遗传算法局部搜索能力差的缺陷，把单纯形法嵌入到遗传算法中构成复合遗传算法，建立了基于遗传单纯形神经网络的大坝变形监控模型。实例研究表明，该模型较遗传神经网络模型、BP模型收敛性能好，具有较高的预报精度、较快的训练速度和较强的泛化能力，用于大坝变形预测有效可行，具有良好的应用前景。 |
| 关 键 词： | 水利工程管理 大坝变形监测 遗传算法 神经网络 单纯形法 |
| 收稿时间： | 2006-03-29 |
| 修稿时间： | 2006-03-29 |
Dam deformation monitoring model based on neural network with genetic algorithm simplex method |
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| YAN Bin,ZHOU Jing,GAO Zhenwei.Dam deformation monitoring model based on neural network with genetic algorithm simplex method[J].Journal of Hydroelectric Engineering,2007,26(4):110-114. | |
| Authors: | YAN Bin ZHOU Jing GAO Zhenwei |
| Affiliation: | 1. College of Civil and Hydraulic Engineering, Dalian University of Technology, Dalian 116024; 2. College of Water Conservancy, Shenyang Agricultural University, Shenyang 110161 ; 3. Water Conservancy Department of Liaoning Province, Shenyang 110003 |
| Abstract: | Considering the poor local search ability of genetic algorithm, simplex method is combined with genetic algorithm to form hybrid genetic algorithm, and then the dam deformation monitoring model based on neural network with genetic algorithm simplex method is established. The example shows that the neural network model with genetic algorithm simplex method owns good convergent rate, high prediction accuracy, fast training speed and superior generating ability compared with the genetic algorithm neural network model and BP neural network model. This method is feasible and effective for dam deformation prediction and has wide applied prospect as well. |
| Keywords: | management of water conservancy project dam deformation monitoring genetic algorithm neural network simplex method |
| 本文献已被 CNKI 维普 万方数据 等数据库收录！ | |
