Machine learning and earthquake forecasting-next steps.
Where this comes from
- Record sourced from PubMed, PMID 34362887.
- Also identified by DOI 10.1038/s41467-021-24952-6 and PMC identifier 8346575.
- Licence recorded as CC BY.
- The licence permits redistribution, so the abstract is shown in full and the full text is available from the publisher.
Abstract
A new generation of earthquake catalogs developed through supervised machine-learning illuminates earthquake activity with unprecedented detail. Application of unsupervised machine learning to analyze the more complete expression of seismicity in these catalogs may be the fastest route to improving earthquake forecasting.