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《Port Engineering Technology》 2010-05
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Application of Improved BP Neural Network in Prediction of Settlement of Roadbed

Guo Yayu1,2,Sun Ligong1,Su Zhaoren3(1.Shanxi Railway Institute,Weinan Shanxi 714000,China;2.School of Civil Engineering,Lanzhou Jiaotong University,Lanzhou Gansu 730070,China;3.No.3 Engineering Company Ltd.of CCCC First Harbor Engineering Company Ltd.,Dalian Liaoning 116001;China)  
Addressing the shortcomings of the traditional BP neural network,the author proposes a new method of prediction by means of back-propagation(BP)neural network which is based on genetic optimization and variable gradient back propagation.The coupling model of genetic algorithm and back-propagation(BP) neural network was applied to the Prediction of Roadbed Settlement,aiming at overcoming shortcomings of the BP neural network model,such as susceptibility of falling into local minimum value and being slow in convergence.Based on field measured data,the comparisons of new model with exponential curve model,hyperbolic model,grey forecasting model and traditional BP neural network prediction model,have shown that the improved BP neural network is of highest accuracy,and adaptable to wide range of applications.
【CateGory Index】: U416.1
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