Research progress in artificial intelligence earthquake prediction

Chen LI, LianQing ZHOU, MengQiao DUAN, ZiYi LI, Na ZHANG, MaoFa WANG

Prog Geophy ›› 2026, Vol. 41 ›› Issue (3) : 997-1018.

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Prog Geophy ›› 2026, Vol. 41 ›› Issue (3) : 997-1018. DOI: 10.6038/pg2026JJ0202

Research progress in artificial intelligence earthquake prediction

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Abstract

This article provides an overview of recent advances in conventional earthquake prediction research alongside the current status of artificial intelligence applications in seismology. It explores the role of AI in the extraction of precursory anomalies, its application in short-term and imminent earthquake forecasting, its utility in medium-to long-term seismic hazard assessment, and its use in aftershock prediction. Research indicates that artificial intelligence technology can rapidly analyze real-time data and effectively identify seismic precursor signals. By integrating spatiotemporal features, AI can recognize subtle anomalous seismic patterns that are difficult to capture with non-AI methods, thereby improving the accuracy of earthquake prediction. However, current earthquake prediction research is still limited by factors such as data quality, model interpretability, computational cost, and cross-regional generalization ability. Future research should focus on exploring physics-informed artificial intelligence learning methods, enhancing multi-modal data fusion, and improving model interpretability. Emphasis should also be placed on translating prediction outcomes into practical applications for disaster early warning and risk assessment. Furthermore, AI technology shows significant potential in aftershock prediction research and, by leveraging the regular patterns of post-mainshock sequences, is poised to become a breakthrough area for the broader field of earthquake prediction.

Key words

Short-term prediction / Medium- to long-term prediction / Aftershock prediction / Artificial intelligence

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Chen LI , LianQing ZHOU , MengQiao DUAN , et al . Research progress in artificial intelligence earthquake prediction[J]. Progress in Geophysics. 2026, 41(3): 997-1018 https://doi.org/10.6038/pg2026JJ0202

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