Application of XGBoost model for early prediction of earthquake magnitude from waveform data
Author:
Funder
Ministry of Earth Science
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12040-023-02210-1.pdf
Reference69 articles.
1. Alexandridis A, Chondrodima E, Efthimiou E, Papadakis G, Vallianatos F and Triantis D 2014 Large earthquake occurrence estimation based on radial basis function neural networks; IEEE Trans. Geosci. Remote Sens. 52 5443–5453.
2. Allen R V 1978 Automatic earthquake recognition and timing from single traces; Bull. Seismol. Soc. Am. 68 1521–1532, https://doi.org/10.1007/BF02247958.
3. Allen R M and Kanamori H 2003 The potential for earthquake early warning in southern California; Science 300 786–789.
4. Allen R M, Gasparini P, Kamigaichi O and Böse M 2009 The status of earthquake early warning around the world: An introductory overview; Seismol. Res. Lett. 80 682–693.
5. Alves E I 2006 Earthquake forecasting using neural networks: Results and future work; Nonlinear Dyn. 44 341–349.
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