A paradigm for developing earthquake probability forecasts based on geoelectric data

Hong Jia Chen, Chien Chih Chen, Guy Ouillon, Didier Sornette

研究成果: 雜誌貢獻期刊論文同行評審

4 引文 斯高帕斯(Scopus)

摘要

We examine the precursory behavior of geoelectric signals before large earthquakes by means of a previously published algorithm including an alarm-based model and binary classification [H.-J. Chen, C.-C. Chen, Nat. Hazards 84, 877 (2016)]. The original method has been improved by removing a time parameter used for coarse-graining of earthquake occurrences, as well as by extending the single-station method into a joint-stations method. Analyzing the filtered geoelectric data with different frequency bands, we determine the optimal frequency bands of earthquake-related geoelectric signals featuring the highest signal-to-noise ratio. Based on significance tests, we also provide evidence of a relationship between geoelectric signals and seismicity. We suggest using machine learning to extract this underlying relationship, which could be used to quantify probabilistic forecasts of impending earthquakes and to get closer to operational earthquake prediction.

原文???core.languages.en_GB???
頁(從 - 到)381-407
頁數27
期刊European Physical Journal: Special Topics
230
發行號1
DOIs
出版狀態已出版 - 1月 2021

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