≡ GMRA-System

The Global Seismic Monitoring and Risk Assessment System (GMRA-v1.0) is a predictive model for seismic and volcanic monitoring. The program's algorithms are based on predictive analytics (machine learning) and the statistical analysis of data from the ISC (International Seismological Centre), NASA, and astronomical events. Calculations utilize the principles of orbital mechanics and historical seismological data (from 2011-01-01). The fundamental basis of the program is the Law of Conservation of Momentum.

GMRA-v1.0 cannot distinguish between volcanic eruptions and earthquakes. Manual statistical analysis has revealed ambiguous results that cannot be ignored. For example, the system successfully detected the impending disasters a day in advance for both the Haiti 2021 and Turkey 2023 earthquakes. However, it also reacts strongly to long-period swarms of global earthquakes with magnitudes between 5.0 and 6.5. In such situations, it is quite difficult to interpret the exact nature of the threat.

For instance, before the Hunga Tonga-Hunga Ha'apai volcanic eruption on January 15, 2022, the indicators displayed an almost surreal scenario (8 active triggers) with a probability forecast of slightly over 90%. Similarly, an earthquake (~M4) registered in northern Israel near dormant volcanoes on January 23 showed a comparable forecast: around 80% probability and 6 to 7 active triggers. The system interprets background seismic activity (a swarm of M5.0-6.0 earthquakes) as a high-threat level (indicating an ~80% probability of an M6.5+ earthquake), which does not always correspond to actual tectonic reality. At this stage (for version 1.0), we are slightly dampening the system's outputs. The mathematical dampening algorithms are detailed below.

Data Processing & Daily Cycles

To maintain mathematical integrity and prevent data leakage, the predictive algorithm operates exclusively on completed 24-hour cycles. Therefore, the historical seismic window used for "Today's" forecast physically ends "Yesterday." While the global map visualizes recent earthquakes in real-time via USGS feeds, the core predictive backend aggregates data and recalculates scoring weights only once daily. Transitioning to hourly forecasting intervals (a potential GMRA-System v2.0) would require a major architectural shift, multiplying the computational load and data volume.