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Computer Engineering ›› 2010, Vol. 36 ›› Issue (16): 16-17. doi: 10.3969/j.issn.1000-3428.2010.16.006

• Networks and Communications • Previous Articles     Next Articles

Prediction Method for Ground Subsidence of Foundation Pit Excavation

HU Min, LIU Wei   

  1. (Sydney Institute of Language and Commerce, Shanghai University, Shanghai 201800)
  • Online:2010-08-20 Published:2010-08-17

一种基坑施工地面沉降预测方法

胡 珉,刘 玮   

  1. (上海大学悉尼工商学院,上海 201800)
  • 作者简介:胡 珉(1970-),女,副教授、博士,主研方向:智能信息处理;刘 玮,硕士研究生
  • 基金资助:

    Gray Model(GM)| Gene Expression Programming(GEP)| ground subsidence| inclinometer

Abstract:

In order to predict the surrounding ground settlement of deep foundation pit excavation accuracy, a new method GGEP(Grey Gene Expression Programming) is proposed to predict the surrounding ground settlement of deep foundation pit excavation, which combines Gene Expression Programming(GEP) with Gray Model(GM). The new model is verified by Shanghai Metro engineering. Experimental results show it is higher goodness of fit with actual monitor data than traditional method. Not only its forecasting accuracy is higher, but also it can self-study to adapt new environment.

摘要:

针对深基坑地面沉降难以有效预测的问题,结合灰色理论和基因表达式编程方法,提出一种新的基坑周边地面沉降预测方法——灰色基因表达式编程算法,并将其应用到上海地铁11号线曹杨路地铁车站基坑施工的数据验证中。实验结果表明,根据该方法获得的地面沉降预测值具有很好的预测精度,其与实测值之间吻合度高于传统方法,同时该方法具有根据实测数据进行自我学习的能力。

关键词: 灰色模型, 基因表达式编程, 地面沉降, 测斜

CLC Number: