App. Res. of Comp. Accepted Paper
Vol. 44, 2027 No. 2

Seismic signal classification method based on multi-scale temporal residual attention network

Du Ruishan1,2,3
Guo Jiansheng1
Meng Lingdong3
1. School of Computer and Information Technology, Northeast Petroleum University, Daqing 163318, China
2. Heilongjiang Provincial Key Laboratory of Petroleum Big Data and Intelligent Analysis, Daqing 163318, China
3. Heilongjiang Provincial Key Laboratory of Integrity Evaluation of Underground Oil and Gas Reservoir Storage, Daqing 163318, China
DOI: 10.19734/j.issn.1001-3695.2026.06.0173

Abstract

Natural earthquakes, explosions, and collapses often show similar waveform characteristics and are easily affected by noise, making reliable classification difficult. To address this issue, we propose a Multi-scale Temporal Residual Attention Network (MTRA-Net) for three-component seismic waveforms. The model combines multi-scale temporal residual feature extraction, channel attention, and global dual-statistics representation to enhance discriminative waveform features. Experiments show that MTRA-Net outperforms Feature-SVM, DeepQuake, CNN-waveform, and EQTypeNet in accuracy, precision, recall, and Macro-F1, while maintaining a good balance between classification performance and inference efficiency. The results demonstrate its effectiveness for automatic classification of natural earthquakes, explosions, and collapses.

Foundation Support

国家重点研发计划项目(2022YFE0206800)
黑龙江省职业教育和继续教育教学改革研究项目(SJGZY2024301)
东北石油大学人才引进科研启动经费项目(13051202402)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2026.06.0173
Publish at: Application Research of Computers Accepted Paper, Vol. 44, 2027 No. 2

Publish History

[2026-10-22] Accepted Paper

Cite This Article

杜睿山, 郭建胜, 孟令东. 多尺度时域残差注意力网络的地震信号分类方法 [J]. 计算机应用研究, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0173. (Du Ruishan, Guo Jiansheng, Meng Lingdong. Seismic signal classification method based on multi-scale temporal residual attention network [J]. Application Research of Computers, 2027, 44 (2). (2026-10-24). https://doi.org/10.19734/j.issn.1001-3695.2026.06.0173. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

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