东南大学学报（自然科学版）2026，Vol.56Issue(3)：399-406,8.DOI:10.3969/j.issn.1001-0505.2026.03.008
基于概率机器学习的大跨度桥梁台风效应预测方法对比研究
Comparative study of probabilistic machine learning approaches for predicting typhoon effects on long-span bridges
摘要
Abstract
Accurate and efficient prediction of wind-induced responses in long-span bridges is critical for en-suring their wind-resistant safety and operational performance.To address the challenges of unstable predic-tion accuracy,weak uncertainty characterization,and poor real-time applicability in existing methods,the Su-tong Bridge was employed as the research case,and eight probabilistic machine learning models were adopted to predict typhoon effects based on the decade-long datasets of typhoons and their effects collected from the bridge site.The predictive performance of these models was comprehensively compared in terms of prediction accuracy,uncertainty quantification,and computation efficiency.The results indicate that deep ensemble-based models significantly reduce prediction errors and achieve the highest prediction accuracy.Compared with other probabilistic machine learning models,such models also exhibit superior uncertainty quantification performance.Despite the variations in training time across different models,all require only minimal testing time,demonstrating the feasibility of rapid prediction of typhoon effects using probabilistic machine learning approaches.关键词
大跨度桥梁/台风效应/概率机器学习/预测性能/结构健康监测Key words
long-span bridges/typhoon effects/probabilistic machine learning/predictive performance/structural health monitoring分类
交通工程引用本文复制引用
李昊卿,张一鸣,王浩,董华能,朱志伟..基于概率机器学习的大跨度桥梁台风效应预测方法对比研究[J].东南大学学报（自然科学版）,2026,56(3):399-406,8.基金项目
国家重点研发计划资助项目(2024YFC3014103) （2024YFC3014103）
国家自然科学基金资助项目(52338011) （52338011）
东南大学新进教师科研启动经费资助项目(RF1028624058) （RF1028624058）
东南大学学科交叉青年特支计划资助项目. （）
