水力发电学报2025，Vol.44Issue(4)：42-49,8.DOI:10.11660/slfdxb.20250405
水电工程施工安全隐患类别辅助校正方法
Auxiliary correction methods for categories of potential safety hazards in hydropower project construction
摘要
Abstract
To enhance the investigation and management of potential hazards in hydropower construction,workers can use mobile reporting to announce safety hazards promptly.However,hazard classification and its accuracy are often subjective,and manual correction is time-consuming and labor-intensive.To mitigate confusion in hazard management during construction,this paper describes a NRBO-CNN-BiLSTM method for auxiliary correction of the mobile phone-reported hazard categories.First,safety hazard data are tokenized,preprocessed,and converted into word vectors,followed by normalization.Then,we apply an attention mechanism to enhance the feature representation capability,and construct a safety hazard classification model using convolutional neural networks and bidirectional long-short-term memory networks.Finally,we work out a Newton-Raphson optimization algorithm to train the model for optimal parameters selection.Case studies demonstrate the probability is 69.2%for the classification of 18 types of hazards.The main reason lies in a relatively low frequency of certain hidden danger categories.In the tests of 6 hazard categories with balanced datasets,our new model achieves a classification probability of 94.6%,a recall value of 94.6%,and an F1 score of 94.6%.The accuracies of these indexes are superior to those of alternative classification models,indicating this correction model is effective and better.关键词
水电工程/随手拍/施工安全/安全隐患/文本分类Key words
hydropower project/snapshoot/construction safety/potential safety hazards/text classification分类
水利科学引用本文复制引用
卢冰,陈述,曹坤煜,陈云,聂本武..水电工程施工安全隐患类别辅助校正方法[J].水力发电学报,2025,44(4):42-49,8.基金项目
国家自然科学基金(52479127 （）
52209163) （）
湖北省自然科学基金计划青年A类项目(2025AFA074) （2025AFA074）
