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Research on the Application of AI in Earthquake Prediction and Early Warning Systems

Author(s)

Zhongyu Wang

Affiliation(s)

School of Civil Engineering, University of Leeds, Leeds, LS2 8AR, United Kingdom *Corresponding Author

Abstract

With the rapid advancement of artificial intelligence (AI) technology, its application in seismology is progressively transforming traditional paradigms of earthquake prediction and early warning. By systematically reviewing literature published since 2015, this paper analyzes the core roles, research progress, and limitations of AI technologies in earthquake prediction and early warning across four dimensions: data-driven seismic feature extraction, machine learning prediction models, real-time warning system optimization, and ethical and technical challenges. The literature indicates that AI significantly enhances seismic signal recognition accuracy and reduces warning response times. However, challenges such as generalization capabilities, interpretability, and ethical risks require further exploration. Future research should focus on multimodal data fusion, edge computing deployment, and the establishment of international collaboration frameworks.

Keywords

Artificial Intelligence; Earthquake Prediction; Early Warning Systems; Machine Learning; Ethical Challenges

References

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