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Research on Application of GA and ANN in Dam Security Monitoring

Author: ChenWei
Tutor: YangZhiQiang
School: Chang'an University
Course: Geodesy and Survey Engineering
Keywords: dam monitoring Artificial Neural Network (ANN) Genetic Algorithm (GA) GA-LMBP Network Model
CLC: TV698.1
Type: Master's thesis
Year: 2009
Downloads: 337
Quote: 1
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Abstract


With the rapid development of economy in China,to develop water resources and solve problems in the construction of water conservancy and hydropower projects will be more and more,especially the dam will increase.Dam safety monitoring is the key to the dam safety management.It is an important means to reduce project risks and accidents,to reveal the actual work of the dam.The analysis of dam monitoring data is the scientific basis to determine the safety of the dam.To make the analysis of observation data on the dam timely、reasonably and effectively is one of the important works of dam safety monitoring.Xiaolangdi water control pivot is the key project of Yellow River,state "85" key projects, since the use of water-storage,it has played a huge social and economic benefit.In order to ensure the safe,strengthening the safety monitoring,and prototype monitoring data analysis is very important.Artificial Neural Network(ANN) and Genetic Algorithm(GA) in dam safety monitoring field has its unique advantages,through the complementary advantages,I establish a kind of GA—LMBP network model of dam safety monitoring prediction,that based on the combination of GA and ANN in this paper,and realizing by programming on the Matlab 7.1 software.The Xiaolangdi dam is a large-scale earth-rockfill dam,relative to the concrete dam, because construction materials and construction of different ways,its deformation value larger、more complex,In the past,the grey system model,the time series model et al usually used in dam monitoring and forecast,but the forecast effect often not ideal.This paper use the GA—LMBP network model of dam safety monitoring prediction in Xiaolangdi dam prototype monitoring data analysis and prediction.At first,in one-dimensional of vertical deformation analysis forecasting,compare with classical BP Neural Network model and the improvement of the forecast of LM—BP network model effect in detailed,found in GA—LMBP network model has obvious advantages,whether in convergence speed and stability,or in the forecast accuracy convergence and stability.Then,the paper further analysis and forecast of the dam deformation of three-dimensional also made good forecast effect.Proved that GA—LMBP network model can well applied in the safety monitoring of earth-rockfill dam.Provide a new forecast model for the earth-rockfill dam deformation analysis.

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CLC: > Industrial Technology > Hydraulic Engineering > Water control,hydraulic structures > Hydraulic structures management > Monitoring of hydraulic structures and prototype observation
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