摘要
在应用软科学理论于岩土工程问题变形预测与分析的基础上,结合润扬长江公路悬索大桥北锚碇基础所进行的施工变形监控与预测工作实践,在现场系统开展了对该处特深、特大型锚碇基坑变形的人工智能神经网络多步滚动预测研究,保证了工程施工的安全及其环境维护。进而,与常规采用的传统方法相比,论述了本项研究的创意性。本文采用工程实录方式作了扼要表述。
On the basis of soft science theory used in the field of geoengineering projects, a MATLAB system-based integrated ANN multi-step deformation prediction in construction has been developed. The study of a deep excavation work-North anchor-block abutment ( foundation ) of the Runyang suspension Bridge reveals that the results of prediction have a good agreement with the monitoring data during insitu measurement. The prediction work ensures the safety under construction and safeguards the environment nearby excavation work .Thus , the study in this article proves that the method suggested here is feasible for deformation prediction in such excavation construction work . This article gives a brief presentation in the form of a case history study.
出处
《岩土力学》
EI
CAS
CSCD
北大核心
2003年第S2期1-7,共4页
Rock and Soil Mechanics
关键词
润扬大桥
智能方法
人工神经网络
锚碇基础
基坑工程
施工变形
预测与监控
Runyang Yangzi River Bridge
intelligent method
artificial neural network (ANN)
anchor block-abutment foundation
excavation work
deformation in construction
prediction and control