广西科技大学学报2024，Vol.35Issue(2)：32-39,8.DOI:10.16375/j.cnki.cn45-1395/t.2024.02.005
基于遗传算法的BP神经网络在轻质路基沉降预测中的应用
Application of BP neural network based on genetic algorithm in settlement prediction of light subgrade
摘要
Abstract
In order to better understand the settlement and deformation of light subgrade construction,a model based on BP neural network was established by selecting monitoring data of a section of the light subgrade settlement from Ning-Wu-Bao-Tong line and optimized by using genetic algorithm.Then the optimized model was used in the settlement prediction of light subgrade.The results showed that the BP neural network optimized by the genetic algorithm had obvious advantages in terms of global search ability and convergence ability.The majority of prediction results had a relative error within a lower range of errors.The evaluation indexes of MAE,RMSE and MAPE were 0.017 mm,0.021 mm and 0.679%respectively for monitoring point 1,and 0.013 mm,0.016 mm and 1.395%respectively for monitoring point 2.The prediction model had a high fitting degree,low error,and strong generalization ability.Therefore,the settlement prediction model optimized by genetic algorithm has reliable prediction effectiveness and accuracy,and is highly feasible in practical engineering.It can be used as auxiliary means of light subgrade settlement prediction and early warning.关键词
轻质路基/地基沉降/预测/遗传算法/BP神经网络Key words
light subgrade/subgrade settlement/prediction/genetic algorithm/BP neural network分类
建筑与水利引用本文复制引用
沈璐,陈修和,陶文斌,李健斌..基于遗传算法的BP神经网络在轻质路基沉降预测中的应用[J].广西科技大学学报,2024,35(2):32-39,8.基金项目
深部煤矿采动响应与灾害防控国家重点实验室资助项目(SKLMRDPC21KF13) （SKLMRDPC21KF13）
国家自然科学基金青年科学基金项目(52008122)资助 （52008122）
