期刊文献+

基于高频组合片段-基因表达式编程算法的轨道交通地面沉降预测模型

Land Subsidence Prediction Model of Rail Transit Based on High-frequency Combination Segment-Gene Expression Programming Algorithm
下载PDF
导出
摘要 [目的]地面沉降预测和控制是轨道交通盾构法隧道施工中最为关注的问题之一。为了解决现有地面沉降预测和控制中存在的模型表达过于复杂且缺乏解释性的问题,需要一种既简洁清晰,又能够描述复杂问题的可解释模型,GEP(基因表达式编程)算法提供了这种可能性,因此需对基于HFS(高频组合片段)-GEP算法的轨道交通地面沉降预测模型进行深入研究。[方法]以杭绍城际铁路某区段盾构隧道工程为依托,选取盾构施工过程中的土舱压力、刀盘扭矩、刀盘转速、推进速度、总推力、隧道埋深及盾尾注浆量等参数作为关键输入型施工参数,地面沉降作为输出型施工参数,通过备选公式集筛选以及HFS选取,建立基于HFS-GEP算法的轨道交通地面沉降预测模型。利用该模型对第180环—第210环区段的关键施工参数进行优化调整,分析盾构施工参数变化对地面最终沉降的影响效果。[结果及结论]基于HFS-GEP算法的地面沉降预测模型可以反映盾构施工参数与地面最终沉降的显式关系;相较于传统GEP算法的地面沉降预测模型,该模型准确度更高,结构更为简洁,且收敛速度更快。通过对盾构关键施工参数进行优化调整,该模型可将第180环—第210环区段的最终沉降量控制在10 mm以内。 [Objective]Land subsidence prediction and control is one of the most concerned issues in rail transit shield tunnel construction.In order to solve the complex and poor interpretable problem of the model expression in the existing land subsidence prediction and control,an interpretable model that is concise,clear,and capable of describing complex problems is needed.GEP(gene expression programming)algorithm provides this possibility,so it is necessary to study in depth the rail transit land subsidence prediction model based on HFS(high frequency segment)-GEP algorithm.[Method]Based on the shield tunnel project of a certain shield tunnel section in Hangzhou-Shaoxing Intercity Railway,parameters such as earth chamber pressure,cutterhead torque,cutterhead speed,advancing speed,total thrust,tunnel buried depth and shield tail grouting amount during shield construction are selected as key input construction parameters,with land subsidence as the output construction parameter.Through alternative formula set screening and HFS selection,a land subsidence prediction model of rail transit based on HFS-GEP algorithm is established.Key construction parameters of the 180th-210th section are optimized and adjusted with the model,and effect of the shield construction parameters change on the final land subsidence is analyzed.[Result&Conclusion]The land subsidence prediction model of rail transit based on HFS-GEP algorithm can reflect the explicit relationship between shield construction parameters and final land subsidence.Compared with the traditional GEP algorithm model,this model has higher accuracy,simpler structure and faster convergence.By optimizing and adjusting the key construction parameters of the shield,the final subsidence of the 180th-210th section can be controlled within 10 mm.
作者 胡珉 卢孟栋 HU Min;LU Mengdong(SHU-UTS SILC Business School,Shanghai University,201800,Shanghai,China;SHU-SUCG Research Center for Building Industrialization,Shanghai University,200072,Shanghai,China)
出处 《城市轨道交通研究》 北大核心 2024年第8期206-210,共5页 Urban Mass Transit
基金 上海市科学技术委员会项目(20DZ2251900)。
关键词 轨道交通 地面沉降预测模型 高频组合片段 基因表达式编程算法 rail transit land subsidence prediction model high-frequency combination fragments gene expression programming algorithm
  • 相关文献

参考文献6

二级参考文献58

共引文献581

相关作者

内容加载中请稍等...

相关机构

内容加载中请稍等...

相关主题

内容加载中请稍等...

浏览历史

内容加载中请稍等...
;
使用帮助 返回顶部