- S21A: Integrating Physical, Statistical, and AI-Enhanced Methods in Seismic Hazard: Toward Real-Time Forecasting of Natural and Induced Earthquakes II Oral
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NOLA CC
Primary Convener:Generic 'disconnected' Message
Davide Zaccagnino, Istituto Nazionale di Geofisica e Vulcanologia
Convener:
Ilaria Spassiani, INGV National Institute of Geophysics and Volcanology
Robert Shcherbakov, University of Western Ontario
Jiancang Zhuang, Institute of Statistical Mathematics
Giuseppe Petrillo, Institute of Statistical Mathematics
Early Career Convener:
Davide Zaccagnino, Sapienza University of Rome
Chair:
Davide Zaccagnino, Sapienza University of Rome
Ilaria Spassiani, INGV National Institute of Geophysics and Volcanology
Robert Shcherbakov, University of Western Ontario
Statistical seismology has taken impressive advances during the last few decades thanks to the incorporation of empirical observations within modelling of seismicity and the empowerment of new techniques and mathematical tools. However, our understanding of earthquake physics is still poor and our ability to forecast major events is limited. This session is devoted to discussing original methods and integrated techniques combining mathematical, physical and AI-based approaches for enhancing earthquake forecasts and catalogue simulations. Research works about the following topics are welcome:1) Modeling of large earthquakes as extreme events. 2) Stochastic earthquake simulations. 3) Stochastic and physics-based methods for forecasting induced and volcano seismicity. 4) Application of physics-informed neural networks to earthquake forecasting. 5) Statistical and physics-informed time-dependent earthquake forecasting. 6) Early-warning and short-term earthquake forecasts based on statistical, physics-informed and AI-enhanced modeling. 7) Modeling long-term recurrence of large earthquakes. 8) Earthquake hazard communication and results in regional seismic hazard.
Index Terms
3245 Probabilistic forecasting
4313 Extreme events
4316 Physical modeling
7223 Earthquake interaction, forecasting, and prediction
Suggested Itineraries:
Disasters‚ Calamities and Extreme Events
Science Communications
Machine Learning and AI
Global Impacts‚ Solutions‚ & Policies
Cross-Listed:
NH - Natural Hazards
T - Tectonophysics
NG - Nonlinear Geophysics
V - Volcanology‚ Geochemistry and Petrology
Neighborhoods:
2. Earth Interior
Scientific DisciplineSuggested ItinerariesNeighborhoodTypeWhere to Watch
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