App. Res. of Comp. Accepted Paper
Vol. 43, 2026 No. 7

Enhanced spatio temporal attention framework for risk attribution on dynamic graphs

Sun Xinjuana
Zhu Yongchaoa
Li Hairuib
a. School of Electronic Engineering, b. Institute for Advanced Study of Digital Twin Water Resources, North China University of Water Resources and Electric Power, Zhengzhou 450046, China
DOI: 10.19734/j.issn.1001-3695.2025.10.0472

Abstract

Spatio temporal graph forecasting faces challenges from coupled dependencies, static weights, and lack of interpretability. To address these issues, this study developed an Enhanced Spatio Temporal Attention Model (ESTAM) , an interpretable framework for dynamic graph risk attribution. The model employed a parallel decoupled architecture to independently capture heterogeneous spatio temporal dependencies. It further introduced a multi-task learning paradigm that integrates risk prediction and causal diagnosis to achieve a paradigm shift from "prediction" to "attribution. " A composite loss function including a boundary loss was designed to enhance robustness. Experimental results showed that the proposed model achieved 93.9% accuracy and a 0.933 weighted F1-score on a simulated dataset, significantly outperforming baselines like GCN and SOTA models like PDFormer. This framework provides a high-performance, interpretable solution for complex dynamic systems and lays a foundation for building trustworthy AI applications.

Foundation Support

国家重点研发计划(2024YFC3210800)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2025.10.0472
Publish at: Application Research of Computers Accepted Paper, Vol. 43, 2026 No. 7

Publish History

[2026-03-25] Accepted Paper

Cite This Article

孙新娟, 朱永超, 李海瑞. 用于动态图风险溯源的增强型时空注意力框架 [J]. 计算机应用研究, 2026, 43 (7). (2026-03-27). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0472. (Sun Xinjuan, Zhu Yongchao, Li Hairui. Enhanced spatio temporal attention framework for risk attribution on dynamic graphs [J]. Application Research of Computers, 2026, 43 (7). (2026-03-27). https://doi.org/10.19734/j.issn.1001-3695.2025.10.0472. )

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  • Application Research of Computers Monthly Journal
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    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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