Articles | Volume 22, issue 6
https://doi.org/10.5194/nhess-22-1931-2022
https://doi.org/10.5194/nhess-22-1931-2022
Research article
 | 
09 Jun 2022
Research article |  | 09 Jun 2022

Hidden-state modeling of a cross-section of geoelectric time series data can provide reliable intermediate-term probabilistic earthquake forecasting in Taiwan

Haoyu Wen, Hong-Jia Chen, Chien-Chih Chen, Massimo Pica Ciamarra, and Siew Ann Cheong

Data sets

Hidden-State Modelling of a Cross-section of Geoelectric Time Series Data Can Provide Reliable Intermediate-term Probabilistic Earthquake Forecasting in Taiwan (V1) S. A. Cheong https://doi.org/10.21979/N9/JSUTCD

Model code and software

HMM_Geoelectric_EQ (v1.0) H. Wen https://doi.org/10.5281/zenodo.6598498

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Short summary
Recently, there has been growing interest from earth scientists to use the electric field deep underground to forecast earthquakes. We go one step further by using the electric fields, which can be directly measured, to separate/classify time periods with two labels only according to the statistical properties of the electric fields. By checking against historical earthquake records, we found time periods covered by one of the two labels to have significantly more frequent earthquakes.
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