长江科学院院报2011，Vol.28Issue(5)：46-49,54,5.
大跨度悬索桥锚碇基础基底土压力智能预测研究
Intelligent Prediction of Anchorage Foundation Soil Pressure for Large Span Suspension Bridge
摘要
Abstract
Intelligent models including Grey Model ( GM ( 1,1 ) ), BP neural network, and the combination of the two models Grey Neural Network Model ( GNNM( 1,1 ) ) were employed in the prediction of anchorage foundation deformation. Monitored soil pressure of the north anchorage foundation of Runyang Bridge was taken to dynamically predict the deformation by these three models. The predictions were further compared with the measured soil pressures. The comparison showed that there is a relative error of 1.11％ ,0.77％ and 0.43％ respectively of each model' s prediction result. Compared with the other two models, the prediction of GNNM ( 1,1 ) was closer to the measured soil pressure, and it can be applied in actual prediction process as it is more appropriate for curve fitting nonlinear data and large-fluctuation data.关键词
锚碇基础/智能算法/变形预测/灰色神经网络Key words
anchorage foundation, intelligent model, soil pressure prediction, gray BP neural network分类
建筑与水利引用本文复制引用
任丽芳,袁宝远..大跨度悬索桥锚碇基础基底土压力智能预测研究[J].长江科学院院报,2011,28(5):46-49,54,5.基金项目
国家自然科学基金委员会、二滩水电开发有限责任公司雅砻江水电开发联合研究项目(50539110) （50539110）
