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Study on the Prediction of Monitoring Information for Deep Foundation Pit Based on Intelligent Algorithm

Author: ChenYanGuo
Tutor: YuanBaoYuan
School: Hohai University
Course: Geological Engineering
Keywords: Deep foundation Neural Networks Genetic Algorithms Simulated annealing Chaos Optimization Forecast
CLC: TU753
Type: Master's thesis
Year: 2006
Downloads: 376
Quote: 4
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Abstract


Deep foundation works with high- cost , high construction difficulty , many unstable factors , the pros and cons of the monitoring system is important to grasp the deep foundation conditions of stability . Deep foundation support system with the surrounding soil combined with each other in a variety of media portfolio of highly complex space systems , deformation and security by the geological conditions , rock and soil properties , site environment , climate change , groundwater dynamics , and other factors impact. Conventional statistical methods are difficult to use monitoring information modeling to predict BP neural network has better nonlinear fitting capability , it has been widely applied in the analysis and prediction of complex nonlinear systems . But BP network has obvious defects , we use a genetic algorithm , simulated annealing hair and mutative scale chaos optimization algorithm to optimize the BP network , forming a series of intelligent algorithms . For excavation monitoring information to establish the non-linear \Freeze construction technology engineering example is the row of piles Jiangsu Runyang Yangtze River Highway Bridge south anchor deep excavation. Based MATLAB7.0 detailed study of BP neural networks, genetic algorithms, simulated annealing algorithm and mutative scale chaos of the basic principle of the intelligent algorithm to optimize the algorithm based on the preparation of the corresponding program ; overall performance of BP network factors for BP network hidden layer nodes is difficult to determine the problem and propose automatic search method , the program design based on MATLB7.0 conduct ; neural networks and genetic algorithms , simulated annealing and chaos optimization algorithm combined with the formation of a series of intelligent algorithm , and is based on MATLAB7.0 the preparation of the program . This intelligent algorithm prediction model is not only suitable for deep excavation engineering the foundation stability Forecast based on monitoring data , but also applies to other aspects of the forecasting problem . Southern anchor deep excavation engineering using freezing piles in construction technology in similar projects in the first case , its difficult to imagine . As a stability guarantee real-time monitoring information feedback is very necessary . In this paper, the several algorithms of the south anchor deep foundation pit monitoring information intelligent predictions . The actual situation shows that the smart algorithm for the problem of the excavation monitoring information forecasting has high accuracy , good guidance for the next step of construction .

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CLC: > Industrial Technology > Building Science > Construction > The project and the type of work > Foundation engineering
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