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AI Reinvents Earthquake Prediction
A recent study led by Társilo Girona from the University of Alaska Fairbanks and Kyriaki Drymoni from Ludwig-Maximilians-Universität has made significant strides in earthquake prediction using machine learning, reports Watchers News. Published in Nature Communications on August 28, 2024, the research introduces a novel technique that analyses seismic data to forecast major earthquakes months in advance. This method builds on the observation that minor, low-magnitude earthquakes may precede larger, more destructive ones.
Improved Accuracy and Potential Applications
The researchers focused on the 2018 Anchorage and 2019 Ridgecrest earthquakes, finding that abnormal seismic activity in the months leading up to these events could predict their occurrence with high accuracy. Their machine learning model detected precursors with up to 85% probability, providing crucial advance warning that could enhance disaster preparedness and public safety.
Future Prospects and Challenges
This predictive technique, currently in its early stages, offers promising potential for improving earthquake forecasting. The approach utilises routine seismic data, making it a feasible tool for real-time monitoring and early warning systems. As the method is refined and validated, many earthquake-prone areas of the Pacific, including PNG; the Solomon Islands; Vanuatu and Tonga, may be able to prevent casualties and destruction, as well as engineer rescue, recovery and response plans as and when the predictions are generated; this would increase resilience and save thousands of lives and properties, as well as public funds.
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