Forecasting characteristic earthquakes in a minimalist model
Miguel Vazquez-Prada, Alvaro Gonzalez, Javier B. Gomez, Amalio F. Pacheco
Abstract
Using error diagrams, we quantify the forecasting of characteristic-earthquake occurrence in a recently introduced minimalist model. Initially we connect the earthquake alarm at a fixed time after the ocurrence of a characteristic event. The evaluation of this strategy leads to a one-dimensional numerical exploration of the loss function. This first strategy is then refined by considering a classification of the seismic cycles of the model according to the presence, or not, of some factors related to the seismicity observed in the cycle. These factors, statistically speaking, enlarge or shorten the length of the cycles. The independent evaluation of the impact of these factors in the forecast process leads to two-dimensional numerical explorations. Finally, and as a third gradual step in the process of refinement, we combine these factors leading to a three-dimensional exploration. The final improvement in the loss function is about 8.5%.
Create a lesson
Related papers
The Glacier Model Intercomparison Project (GlacierMIP): Towards standardisation of global glacier projections
Larissa N. van der Laan, Regine Hock, Johannes Brunner et al.
DiffSpecMatch: Differentiable Waveform Inverse Design with Configurable Optimization Modules for Response-Spectrum Matching of Ground Motions
Xiaohu Hu, Su Chen, Zhijun Dai et al.
Physics-based deep learning for non-stationary adaptive multiple suppression
Chao Li, Yangkang Chen
A Multi-frame Analysis of Flow Reversal in Tidal Bore
Assia Belemkadem, Johan Fourdrinoy, Anthony Beaudoin et al.
Event-Centric Earthquake Monitoring with a Multi-Station Transformer
Haoyu Wang, Weiqiang Zhu
Bayesian Inversion Beyond the Generator's Range: Reducing Non-physical Constraints from Generative Neural Networks
Pratyay Roy, Xuebin Zhao, Andrew Curtis