计算机工程与应用2012，Vol.48Issue(19)：225-229,5.DOI:10.3778/j.issn.1002-8331.2012.19.051
小波神经网络在基坑变形预测的研究与应用
Research and application on prediction deformation of foundation pit based on wavelet neural network
摘要
Abstract
In order to solve the ubiquitous problems on cable-stayed bridge's loading test which are expensive cost and long testing time, this paper builds a practical cable-stayed bridge's finite element model, analyzes the mechanics characteristics of cable-stayed bridge, and puts forward a method of loading test conditions' merging. Finally, Dezhou bridge's loading tests are finished with the merging method. The research results show that for cable-stayed bridges, beam maximum moment condition and beam maximum deflection condition can combine into one condition: and tower maximum moment condition and top tower horizontal displacement can combine into one condition. The merging method can be applied to practical bridge's loading test and can popularize to other long-span bridge type' s loading test. In summery, the research result has a wide application prospect.关键词
基坑变形/工程安全/预测研究/小波神经网络/参数优化Key words
pit deformation/ engineering safe/ predict research/ wavelet neural network/ parameter optimization分类
信息技术与安全科学引用本文复制引用
王博,商岸帆,郭晨,罗超,罗文浪..小波神经网络在基坑变形预测的研究与应用[J].计算机工程与应用,2012,48(19):225-229,5.基金项目
国家自然科学基金(No.61063007) （No.61063007）
江西省教育厅科技计划项目(No.GJJ11530) （No.GJJ11530）
江西省高等学校重点学科项目. （）
