Deliverable 4.3 Machine learning approaches for earthquake detection
Research report
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Date
2024-02-20Metadata
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- NGI report [224]
Abstract
This report is a review of machine learning-based methods for earthquake detection. It first introduces the basic concepts of traditional earthquake detection, and commonly used approaches. It then goes onto describe the concept of artificial intelligence, machine learning, and deep learning. This is followed with a summary of how these concepts are employed to detect earthquakes in seismic data, with a synthesis of the most widely used machine learning detection algorithms. The ways in which machine learning methods could be applied to the activities in the SHARP project are given in the conclusions, along with the future directions of the field.
Series
NGI-rapport;20210518-D4-3SHARP Storage;Deliverable 4.3