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《Journal of Beijing Jiaotong University》 2012-01
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Subgrade settlement prediction of transition section based on momentum back-propagation

WEI Jing1,PU Xingbo1,QIAN Yaofeng2,LI Junchang2(1.School of Civil Engineering,Beijing Jiaotong University,Beijing 100044,China;2.China Railway 21st Bureau,Lanzhou Gansu 730102,China)  
With the momentum back-propagation method,this paper improved the convergence of BP neural network and developed a prediction model for subgrade settlement of transition section.The model overcame the disadvantages of traditional BP neural network,such as slow convergence speed and easy running into local optimum.Based on test data of the transition section between bridge and subgrade in Tianjin-Qinhuangdao high speed railway,this paper compared the optimization model with the traditional BP neural network model.The results indicate that the neural network improved by momentum BP algorithm has higher predictive accuracy,and it can consider multiple influence factors simultaneously.As a consequence,it has broad application prospect.
【Fund】: 中央高校基本科研业务费专项资金资助(2009JBM079);; 2010、2011年大学生创新实验项目资助
【CateGory Index】: U213.157
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