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10 papers analyzed
These studies suggest that predicting and tracking earthquakes and tsunamis can be effectively achieved using a combination of geophysical data, GPS measurements, wave gauge data, and advanced modeling techniques like ANN and MLBP.
20 papers analyzed
Predicting and tracking earthquakes and tsunamis are critical for mitigating their devastating impacts. Various methodologies have been developed to enhance the accuracy and timeliness of these predictions, leveraging advancements in geophysical data, GPS technology, and artificial intelligence.
Integration of GPS and Strong Motion Data:
Multi-Array Back-Projection (BP) Approach:
Artificial Neural Networks (ANN) for Tsunami Forecasting:
Near-Field Tsunami Models:
GPS Ionosphere Observations:
Inverse Algorithms for Tsunami Forecasts:
Coastal GPS Stations:
The integration of advanced geophysical data, GPS technology, and artificial intelligence has significantly improved the prediction and tracking of earthquakes and tsunamis. Combining high-rate GPS and strong motion data, utilizing multi-array back-projection methods, and employing artificial neural networks are among the most effective strategies. Additionally, real-time data from coastal GPS stations and ionospheric observations provide practical and cost-effective solutions for early warnings, enhancing the overall accuracy and timeliness of tsunami forecasts.
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