English

領域外・複数領域 (M)
セッション小記号計測技術・研究手法 (TT)
セッション IDM-TT47
タイトル Interdisciplinary Studies on Pre-Earthquake Processes with Advanced Models, Observations, and AI
タイトル短縮名 Pre-Earthquake Processes
代表コンビーナ 氏名 Yangkang Chen
所属 University of Texas at Austin
共同コンビーナ 1 氏名 John B Rundle
所属 University of California Davis
共同コンビーナ 2 氏名 服部 克巳
所属 千葉大学大学院理学研究院
共同コンビーナ 3 氏名 韓 鵬
所属 南方科技大学
共同コンビーナ 4 氏名 Ouzounov Dimitar
所属 Center of Excellence in Earth Systems Modeling & Observations (CEESMO) , Schmid College of Science & Technology Chapman University, Orange, California, USA
セッション言語 E
スコープ This session highlights recent advances in interdisciplinary research on pre-earthquake processes that combine space- and ground-based observations, physical modeling, and artificial intelligence (AI). Diverse observables, such as deformation (GPS, InSAR), electromagnetic, geochemical, hydrogeological, and ionospheric changes, have been linked to stress evolution in the lithosphere before large earthquakes. The emergence of large language models (LLMs), generative AI, and multi-modal learning frameworks is transforming this field. These tools enable fusion of heterogeneous datasets, generation of synthetic precursors for model testing, and real-time interpretation of complex signals through in-context and physics-informed learning. We invite contributions on observational and modeling results; machine learning and AI-enhanced methods for earthquake forecasting and nowcasting; multi-modal data integration; explainable and physics-informed AI; and advanced sensing and computational technologies. The session aims to connect geophysical, geochemical, and computational communities to accelerate progress toward more reliable, interpretable, and physically grounded earthquake forecasting systems.
セッション形式 口頭およびポスターセッション