RASE: A Real-Time Automatic Search Engine for Anomalous Seismic Electric Signals in Geoelectric Data

Author:

Xue Jiyan1ORCID,Wu Sihong1ORCID,Huang Qinghua1ORCID,Zhao Li1ORCID,Sarlis Nicholas V.2ORCID,Varotsos Panayiotis A.2ORCID

Affiliation:

1. Department of Geophysics, School of Earth and Space Sciences, Hebei Hongshan National Observatory on Thick Sediments and Seismic Hazards, Peking University, Beijing, China

2. Department of Physics, Section of Condensed Matter Physics and the Solid Earth Physics Institute, National and Kapodistrian University of Athens, Athens, Greece

Funder

National Natural Science Foundation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Reference66 articles.

1. Improving the Signal‐to‐Noise Ratio of Seismological Datasets by Unsupervised Machine Learning

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4. Electric Fields that “Arrive” before the Time Derivative of the Magnetic Field prior to Major Earthquakes

5. Batch normalization: Accelerating deep network training by reducing internal covariate shift;ioffe;Proc 32nd Int Conf Mach Learn (ICML),2015

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