GEOLOGICAL HAZARDS AND SCIENTIFIC APPROACHES TO THEIR PREDICTION
Keywords:
Geological hazards, Earthquake prediction, Landslide forecasting, Volcanic eruption monitoring, Seismic networks, Early-warning systems, Machine learning in hazard prediction, Artificial intelligence, Big data analytics, Earthquake early warning systems, Risk management strategies, Hazard mitigation.Abstract
This article examines the current scientific approaches to predicting and mitigating geological hazards, focusing on earthquakes, landslides, and volcanic eruptions. It evaluates the state of prediction technologies, including seismic networks, machine learning algorithms, and early-warning systems, highlighting the progress made as well as the significant limitations that still exist. While real-time monitoring systems and probabilistic models have improved hazard forecasting, the ability to predict large-scale events such as megathrust earthquakes and volcanic eruptions with precision remains a major challenge. The study also explores the potential of emerging technologies like artificial intelligence (AI) and big data analytics to enhance predictive accuracy. Ultimately, the paper underscores the importance of continued technological innovation and interdisciplinary research, alongside preparedness strategies, to reduce the risks and societal impacts of geological disasters.
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