江西建材Issue(6)：174-176,179,4.
基于SSA-BP的深基坑地表变形预测研究
Research on Ground Deformation Prediction of Deep Foundation Pit Based on SSA-BP
石强 1程泷 1杨展 2赵嘉2
作者信息
- 1. 中国水利水电第七工程局有限公司,四川 成都 610213
- 2. 中国地质大学(武汉)工程学院,湖北 武汉 430074
- 折叠
摘要
Abstract
In this study,the sparrow search algorithm was applied to optimize the BP neural network for predicting deformations in monitoring points around a metro station's deep foundation pit in Shenzhen.The training and learning were conducted using 118 periods of monitoring data from monitoring point DBC16-4.The training performance was compared with particle swarm optimization-based BP neural network,genetic algorithm-based BP neural network,and standard BP neural network.The results indicate that the sparrow search algorithm optimizes the weights of the BP neural network with faster speed and higher convergence accuracy.The sparrow search algorithm optimized BP neural network model exhibits an average relative error of only 1.72%,which is lower than other algorithms,demonstrating superior fitting accuracy and excel-lent prediction performance.关键词
深基坑/地表沉降/变形预测/BP神经网络/麻雀搜索算法Key words
Deep foundation pits/Ground settlement/Deformation prediction/BP neural network/Sparrow search algorithm分类
建筑与水利引用本文复制引用
石强,程泷,杨展,赵嘉..基于SSA-BP的深基坑地表变形预测研究[J].江西建材,2024,(6):174-176,179,4.
