优化GM(1,1)模型在桥梁静载试验中应用  

Optimization of Application of GM (1,1) Model in Static Load Test of Bridge

作　　者：梁德襄 LIANG Dexiang

机构地区：[1]中国市政工程西南设计研究总院有限公司,四川成都610036

出　　处：《城市道桥与防洪》2022年第5期202-205,M0018,共5页Urban Roads Bridges & Flood Control

摘　　要：设计一种适用于桥梁静载试验中极不完备数据条件下的优化GM(1,1)模型。使用3个前置神经网络模块替换传统模型中的微分拟合过程,利用神经网络的回归能力对其进行优化,使用1个后置神经网络模块结合1个数据解模糊模块替换传统模型的数据还原过程,其他数据处理方式沿用传统模型的数据处理方式。经过仿真计算,发现不同桥梁设计规模下,优化模型的标准差显著低于传统模型,证实优化模型具有较显著的算力提升。An optimized GM(1,1)model is designed for the static load test of bridge under the condition of extremely incomplete data.Three pre neural network modules are used to replace the differential fitting process in the traditional model.The regression ability of neural network is used to optimize it.One post neural network module is used to replace the data restoration process of traditional model with one data solving fuzzy module.Other data processing methods are based on the traditional model.Through simulation,it is found that the standard deviation of the optimized model is significantly lower than that of the traditional model under different bridge design scales,which proves that the optimized model has a significant calculation force improvement.

关 键 词：桥梁设计 静载试验 GM(1 1)模型 神经网络 模型优化 

分 类 号：U446[建筑科学—桥梁与隧道工程]