土木工程与管理学报2026，Vol.43Issue(4)：48-53,6.DOI:10.13579/j.cnki.2095-0985.2026.20250498
小样本条件下的施工安全巡查报告文本分析及风险智能判别
Text Analysis and Risk Intelligent Identification of Construction Safety Inspection Reports Under Small Sample Condition
摘要
Abstract
To address the problems of limited sample size and imbalanced category distribution in construction safety inspection reports,this study proposes a BERT-based ensemble text classification method for automatic identification of risk warning levels.Back translation combined with Easy Data Augmentation(EDA)is employed to enrich text samples and alleviate the shortage of minority-class data.On this basis,multiple training subsets are generated through bootstrap sampling,and a Bagging ensemble with a majority voting strategy is adopted to improve prediction stability under small sample condition.In addition,Focal Loss is introduced to reduce the bias toward majority classes during mod-el training.A case study based on safety inspection report from a metro foundation pit project is con-ducted to validate the proposed method.The results indicate that the proposed approach effectively im-proves the classification performance of risk warning levels under small sample and imbalanced data condition,achieving an overall accuracy of 96.24％on the test set.The proposed method provides a feasible technical solution for efficient utilization of textual information in construction safety manage-ment.关键词
施工安全管理/安全巡查报告/小样本文本分类/风险预警/集成学习/BERTKey words
construction safety management/safety inspection report/small sample text classifica-tion/risk warning/ensemble learning/BERT分类
建筑与水利引用本文复制引用
张霄楠,董超,李凯,方雪晴,李达..小样本条件下的施工安全巡查报告文本分析及风险智能判别[J].土木工程与管理学报,2026,43(4):48-53,6.基金项目
国家自然科学基金(72201198) （72201198）
