基于贝叶斯网络结构学习的短期强震危险性概率预测

司震; 袁静; 张博; 陈石

doi:10.3799/dqkx.2025.186

Volume 51 Issue 1

Jan. 2026

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Si Zhen, Yuan Jing, Zhang Bo, Chen Shi, 2026. Probabilistic Prediction of Short-Term Strong Earthquake Hazard Based on Bayesian Network Structure Learning. Earth Science, 51(1): 43-55. doi: 10.3799/dqkx.2025.186

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Si Zhen, Yuan Jing, Zhang Bo, Chen Shi, 2026. Probabilistic Prediction of Short-Term Strong Earthquake Hazard Based on Bayesian Network Structure Learning. Earth Science, 51(1): 43-55. doi: 10.3799/dqkx.2025.186

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Probabilistic Prediction of Short-Term Strong Earthquake Hazard Based on Bayesian Network Structure Learning

doi: 10.3799/dqkx.2025.186

Si Zhen^{1
,
,},
Yuan Jing^{1
,
,
,},
Zhang Bo²,
Chen Shi^{3, 4}

1.
School of Computer Science and Engineering, University of Emergency Management, Sanhe 065201, China
2.
Liaoning Earthquake Agency, Shenyang 110034, China
3.
Beijing Baijiatuan Earth Science National Observation and Research Station, Beijing 100095, China
4.
Institute of Geophysics, China Earthquake Administration, Beijing 100081, China

Received Date: 2025-06-09
Publish Date: 2026-01-25

Abstract

Abstract

To enhance the capability for monthly-scale regional strong earthquake risk prediction, this paper introduces a probabilistic seismic hazard prediction model based on Bayesian network structure learning. Initially, a series of predictive indicators, serving as the nodes of the Bayesian network, are derived from the earthquake catalog. Subsequently, the thresholds for each node and the directed connections among nodes are determined using swarm intelligence algorithms. Ultimately, through parameter estimation, the target node outputs the probability of M_W5.0+ strong earthquakes occurring in the target region within the next month. Experimental results indicate that the model achieves an average prediction efficiency metric of 0.783, and validation via the Molchan test confirms its significant effectiveness, demonstrating the model's capacity to comprehensively explore the latent causal relationships between seismic precursors and strong earthquakes.
- Bayesian network structure learning,
- probabilistic seismic hazard prediction,
- earthquake catalog,
- swarm intelligence algorithms,
- Molchan test,
- seismology

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References(48)

References

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Probabilistic Prediction of Short-Term Strong Earthquake Hazard Based on Bayesian Network Structure Learning

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