同济大学学报（自然科学版）2026，Vol.54Issue(1)：87-97,11.DOI:10.11908/j.issn.0253-374x.24288
基于改进粒子群算法的土参反演及基坑开挖变形预测
Soil Parameter Inversion and Foundation Pit Excavation Deformation Prediction Based on MLAPSO
摘要
Abstract
To overcome the limitations of traditional intelligent optimization algorithms,such as low accuracy,slow convergence,and susceptibility to local optima,this paper proposes a multilevel learning adaptive particle swarm optimization(MLAPSO)algorithm.The algorithm incorporates a best-point set strategy and multiple search mechanisms,including global search,the FDB mechanism,and the Levy flight strategy.Tests on the CEC—2022 benchmark functions demonstrate that MLAPSO significantly outperforms traditional optimization algorithms in terms of search accuracy and stability.Furthermore,combined with the load-structure model of foundation pit excavation,it proposes a method for soil parameter inversion and staged deformation prediction of foundation pits based on MLAPSO.The method is validated using monitoring data from a metro station.Results show that the approach can accurately invert soil parameters,and the predicted deformation of the retaining structures based on these parameters aligns closely with measured deformations,confirming the effectiveness and reliability of the method.关键词
基坑工程/多级学习自适应粒子群算法(MLAPSO)/土体参数反演/基坑变形预测Key words
foundation pit engineering/multilevel learning adaptive particle swarm optimization algorithm(MLAPSO)/soil parameter inversion/foundation pit deformation prediction分类
交通工程引用本文复制引用
何平,官子愈,狄宏规,郭慧吉,吴迪,周俊宏,周顺华..基于改进粒子群算法的土参反演及基坑开挖变形预测[J].同济大学学报（自然科学版）,2026,54(1):87-97,11.基金项目
国家自然科学基金(52278456) （52278456）
