科技创新与应用2025，Vol.15Issue(9)：64-68,5.DOI:10.19981/j.CN23-1581/G3.2025.09.015
改进型小波神经网络在高铁路基沉降精准监测中的应用研究
摘要
Abstract
In view of the limitations of traditional BP neural networks in dealing with complex nonlinear problems,this research is committed to implementing optimization strategies for widely used wavelet neural network models.Specifically,by using high-speed railway subgrade settlement data in the form of time series as input vectors,an enhanced prediction framework is constructed to accurately predict subgrade settlement.The experimental verification process shows that compared with the unimproved wavelet neural network model,the optimized wavelet neural network shows better performance in the settlement prediction task,improving the accuracy and reliability of the prediction results,thereby providing technical support for the safety monitoring and maintenance of high-speed railway infrastructure.关键词
路基沉降/改进小波神经网络/沉降量预测/实验验证/预测框架Key words
subgrade settlement/improved wavelet neural network/settlement prediction/experimental verification/prediction framework分类
交通工程引用本文复制引用
刘攀,王倩..改进型小波神经网络在高铁路基沉降精准监测中的应用研究[J].科技创新与应用,2025,15(9):64-68,5.基金项目
2023年高校教师创新基金项目(2023A-264) （2023A-264）
