东南大学学报（自然科学版）2026，Vol.56Issue(6)：812-819,8.DOI:10.3969/j.issn.1001-0505.2026.06.002
基于改进残差网络的文化遗产区地震监测响应判别方法研究
Study on earthquake monitoring and response discrimination methods in cultural heritage region using improved residual network
摘要
Abstract
To evaluate seismic responses in cultural heritage building complexes,a three-channel residual net-work(TF-ResNet)with an attention mechanism is proposed.The framework employs a residual neural net-work(ResNet)as its backbone,integrating an efficient channel attention module and a joint spatial-channel convolutional attention module.A three-channel parallel input architecture is designed,and multi-source fea-ture fusion is realized through fully connected layers,thereby enhancing the discrimination accuracy of seismic responses.Using the seismic motion data from a group measurement point in a cultural heritage area,the TF-ResNet validation experiments are conducted,and the ablation and comparison tests are carried out with the existing deep learning models.Five evaluation metrics,including the accuracy,precision,recall,F1 score,and confusion matrix,are employed to evaluate the model performance.The results demonstrate that the classification accuracy of the TF-ResNet achieves 90.67%,and the engineering validation accuracy is 92.93%.The TF-ResNet can significantly improve the discrimination accuracy and stability of seismic re-sponses for building complexes,providing a practical technical solution for earthquake monitoring systems.关键词
地震监测/残差网络/图像分类/古建筑保护Key words
earthquake monitoring/residual neural network(ResNet)/image classification/heritage build-ing protection分类
建筑与水利引用本文复制引用
白凡,刘韬,杨娜,孟文哲,旦增格桑..基于改进残差网络的文化遗产区地震监测响应判别方法研究[J].东南大学学报（自然科学版）,2026,56(6):812-819,8.基金项目
中央高校基本科研业务费重点资助项目(2024JBZY017) （2024JBZY017）
国家自然科学基金面上资助项目(52478119) （52478119）
北京交通大学结构风工程与城市风环境北京市重点实验室开放基金资助项目(2024-2). （2024-2）
