高铁桥墩沉降预测模型的研究及应用  

Research on Prediction Model of High-speed Railway Pier Settlement and Its Application

作　　者：李沛鸿[1] 李辰风 刘陶胜[1] 辛四梅 

机构地区：[1]江西理工大学建筑与测绘工程学院,江西赣州341000

出　　处：《地理空间信息》2015年第6期130-131,137,共3页Geospatial Information

基　　金："建筑工程测量"2013年省级质量工程资助项目(SZG-13-03-04)

摘　　要：分析高铁的沉降观测数据,评价其安全状况至关重要。采用基因表达式编程(GEP)算法,将某高铁桥墩的沉降观测数据建立预测模型,并与GM(1,1)模型、灰色线性回归模型及BP神经网络模型进行对比分析。结果表明,基于GEP的方法建模更加便捷,预测精度更高,能有效进行变形分析。As both analyzing measured settlement data of highspeed railway and assessing its running state were critical, we built a prediction model involving GEP algorithm and measured settlement data of a certain high-speed railway pier. And then, we made this model which put out in this paper compared with GM(1,1) model, Gray linear regression model and BP neural network model. The result proves that the method of GEP is much convenient and high-precision than conventional methods to analyze railway deformation effectively.

关 键 词：桥墩沉降 GEP 预测模型 精度 

分 类 号：P258[天文地球—测绘科学与技术]