| 大坝变形监测遗传神经网络模型 |
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| 引用本文： | 王志旺,张保军,李迪,张漫.大坝变形监测遗传神经网络模型[J].岩土力学,2003(Z1). |
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| 作者姓名： | 王志旺 张保军 李迪 张漫 |
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| 作者单位： | 中国地质大学，长江科学院大坝安全监测研究所，长江科学院大坝安全监测研究所，长江科学院大坝安全监测研究所 湖北武汉430074长江科学院大坝安全监测研究所，湖北武汉430010，湖北武汉430010，湖北武汉430010，湖北武汉430010 |
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| 摘 要： | 在简要介绍遗传神经网络的基本概念及学习步骤的基础上,分别对大坝坝顶径向水平位移、切向水平位移和大坝坝顶沉降量监测数据进行了训练和预测。结果表明,利用遗传算法特有的全局优化能力,可以较好地完成网络的学习,而且还减少了网络训练次数,缩短了网络训练时间。
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| 关 键 词： | 人工神经网络 遗传算法 大坝变形监测 预测 |
Dam deformation monitoring model based on genetic algorithm of neural network |
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| WANG Zhi-wang,ZHANG Bao-jun,LI Di,ZHANG Man.Dam deformation monitoring model based on genetic algorithm of neural network[J].Rock and Soil Mechanics,2003(Z1). |
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| Authors: | WANG Zhi-wang ZHANG Bao-jun LI Di ZHANG Man |
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| Institution: | WANG Zhi-wang1,2,ZHANG Bao-jun2,LI Di2,ZHANG Man2 |
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| Abstract: | On the basis of brief introduction of the principle and algorithm of genetic neural network, the forecast model is applied to the monitoring data of tangential horizontal displacement, radial horizontal displacement and settlement of a dam. The result indicates that the forecast model could complete the train and forecast of the network with less training frequency and time by means of overall optimizing ability of genetic algorithm. |
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| Keywords: | artificial neural network genetic algorithm dam deformation monitoring forecast |
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